Alex Bozarth, Luciano Resende: Customizing JupyterLab using extensions | PyData Austin 2019

Andy Terrel: Becoming a Data Head, a reflection on the trade offs and decision | PyData Austin 2019

Ariel Wolfmann: Recommendations at Rappi: from MVP to Data Product | PyData Austin 2019

Bugra Akyildiz: Putting Tensorflow Models into Production | PyData Austin 2019

Chris Leonard: Enhancing Common Natural Language Processing with Cognitive... | PyData Austin 2019

Dalton A. R. Sakthivadivel: How Neuroscience Makes AI Intelligent | PyData Austin 2019

Deeksha Yennam: Multilingual embeddings to scale NLP models to multiple... | PyData Austin 2019

Dharhas Pothina: Building a User Maintainable Visualization Dashboard for... | PyData Austin 2019

Dr. Kevin Horecka: 3 Case Studies in Applying Advanced Technology... | PyData Austin 2019

Fatma Tarlaci, Dhavide Aruliah: An Introduction to Sentiment Analysis of... | PyData Austin 2019

Hao Jin: Accelerate large-scale machine learning with NP on MXNet | PyData Austin 2019

Jacob Barhak: Visualizing Machine Learning of Units of Measure using PyViz | PyData Austin 2019

James A Bednar: Panel: Dashboards for PyData | PyData Austin 2019

James Powell: Objectionable Content | PyData Austin 2019

Jim Crist: Introducting Dask-Gateway: Dask clusters as a service | PyData Austin 2019

Joe Gartner: Addressing the Scarcity of Data Scientist | PyData Austin 2019

Katrina Riehl: Q&A with Keynote Katrina Riehl | PyData Austin 2019

Katrina Riehl: What the...? Data Science Questions Asked and Answered | PyData Austin 2019

Lightning Talks | PyData Austin 2019

Lilly Winfree: Frictionless Data Pipelines | PyData Austin 2019

Luciano Resende, Alan Chin: AI pipelines powered by Jupyter notebooks | PyData Austin 2019

Max Klein, PhD: Working interactively with large and remote datasets in... | PyData Austin 2019

Morgan Cundiff: Develop Data Science for Business Value: a Phoenix Story | PyData Austin 2019

Nicole Carlson: Productionalizing a Data Science Team | PyData Austin 2019

Peter Wang: Values-based OSS Open Discussion | PyData Austin 2019

Pushkar Kumar Jain: Evaluation of Cloud Hosting Frameworks for Machine... | PyData Austin 2019

Saloni Jain: Speeding up Machine Learning tasks using GPUs in Python | PyData Austin 2019

Samuel Taylor: Machine Learning Crash Course | PyData Austin 2019

Saul Shanabrook: metadsl: separating API from execution | PyData Austin 2019

Sudheesh Katkam: Hyperrest: A new Apache Arrow API For High Performance Data... | PyData Austin 2019

Tailai Wen: ADTK: An open-source Python toolkit for anomaly detection in... | PyData Austin 2019

Travis E Oliphant: Extending Python Into the Future | PyData Austin 2019

Travis E Oliphant: uarray: Separating interface from implementation | PyData Austin 2019

Travis Oliphant: Q&A with Keynote Travis Oliphant | PyData Austin 2019

Asyncio in the Wild

Becoming Free by Anna Kazakova Lindegren

Big Data Pipeline Design and Tuning in PySpark by Rockie Yang

Born to adapt: How Dathena solves the industry diversity problem by Tetiana Kodliuk

Equip your performance toolbox Cython vs Pybind11 by Gavin Chan

Expressive coding extravaganza: making art with code by Half Scheidl

From bigger than 1 billion years to smaller than 1 second by Isaac Bernat

Keynote: Stories From Real World Vision Projects by Tess Ferrandez

Keynote: The Ubiquity of Operationalizing Python Models

Learning Python (or Anything) Effectively by Jessica Shortz

Lightning talk 01

Lightning talk 02

Lightning talk 03

Lightning talk 04

Lightning talk 05

Lightning talk 06

Lightning talk 07

Lightning talk 08

Lightning talk 09

Lightning talk 10

Make your Python code fly at transonic speeds! by Ashwin Vishnu Mohanan

Making sense of ML Black Box: Interpreting ML Models Using SHAP

Mutation Testing - Theory and Practice by Anders Hovmöller

PyCon Sweden 2019 closing remarks

PyCon Sweden 2019 Opening

PyMacaron: microservices made easy

Scaling AI @ H&M

Test Fast, Fix More - Property based testing with Hypothesis by Alexander Hultnér

Volumetric sculpting - Shaping a dynamic chisel

What is causal inference, and why should data scientists know? by Ludvig Hult

Why Python is huge in finance? by Daniel Roos

Writing highly scalable and provenanceable data pipelines by Guilherme Caminha

A Pythonista's Approch to DeepFakes - Navin Pai

Accessibility of Python and Data Science - Rishab, Shakul, Abhisar, Sunil

Anomaly Detection in Cyber Security for loT using Federated Learning - Bargava Subramanian

Building GraphQL API with Django - Anitha

Call, Raise or Fold - Python for Simulating Poker Games - Abhijit Gadgil

Demystifying Web Map Servers: The Invisible side of geographic Information Systems - Shivashis Padhi

Entering the world of Serious Games with Python - Harshinee Sriram

Exploring Augmented Reality with Python - Srikar Mutnuri

Extracting tabular data from PDF'S with Camelot & Excalibur - Vinayak Mehta

Generators Explained - Rajat Vadiraj Dwaraknath

How we are building Smart Reply for Chat - Nirant Kasliwal

How we built a State Machine to keep up with a 1200+ Txs/second blockchain protocol - Anomit Ghosh

Indeed's Endeavor to "Push on Green" - Amulya Bandikatla

IndicNLP - Adam Shamsudeen, Kamal Raj, Selva Kumar

Keynote - David Beazley

Keynote - Devi A S L

Keynote - Ines Montani

Keynote - Jake Vanderplas

Let's Hunt a Memory Leak - Sanket

Lifting Up: Deep Learning For Implementing Anti-hunger and Anti-poverty Programs - Usha Rengaraju

Lightning Talk - Bhuvana

Lightning Talk - Eshan Singh

Lightning Talk - Gokul

Lightning Talk - Mohamed Javed - Jetbrains

Lightning Talk - Pradeek - Happyfox

Lightning Talk - Praveen J - AWS

Lightning Talk - Rohan Bhindwale - Bloomberg

Lightning Talk - Senthil

Lightning Talk - Srinivasan

Lightning Talk - Subin Siby | Selfie a Day Project

Lightning Talk - Sunil Kumar - Ericsson

Lightning Talk - Vishwesh K - Mad Street Den

Machine learning Algorithms from scratch in Python - Arjun Kathuria

Machine Learning Bias - AbdulMajedRaja RS

Machine Learning for loT at the Edge - Sukanya Mandal

Machine Learning Model and Dataset Versioning - Kurian Benoy

Maps, Delimitation, and Gerrymandering with Python - Anand S

Micropython: Building a Physical Inventory Search Engine - Vinay Keerthi

Natural Language Generation with Python - Jaidev Deshpande

Performance Optimization with Python Elasticsearch - Anisha Swain & Manaswini Das

Practical Introduction to Graph DBs, Graph Traversals in Python - Srimathi H

Python based simulation and treatment planning in Craniofacial Surgery - Akilesh Ramasamy

Python is NOT easy - Lesson's From Sympy's codebase - Sadhana Srinivasan

Python Packaging - Where We Are and Where We're Headed - Pradyun Gedam

Ragabot - Music Encoded - Vikrant Patil, Harsh Vinjamoor

Real World Numba: Taking the Path of Least Resistance - Ankit Mahato

Scaling up Data Pipelines using Apache Parquet and Dask - Lalit Musmade

"Smart lock? Nah dude.": Pwning a smart lock with Python - Anirudh & Raghav

Solving Industrial Problem with Machine Learning and Image Processing - Sonam Pankaj

spaCy PyTorch Transformers - Matthew Honnibal

Using Vulture to improve used-to-unused code ratio of your Python Programs - Rahul Jha

Visual Studio Code + Python = Awesomeness ! - Ashish Sahu & Sagar Bhanudas Josh

2FA, WTF? - PyCon SG 2019

An introduction to Python for Machine Learning with VS Code and Azure - PyCon SG 2019

Automate the Boring Stuff with Slackbot - PyCon SG 2019

Building an analytics data pipeline using Airflow and PySpark - PyCon SG 2019

Building an interactive training environment using JupyterHub - PyCon SG 2019

Converting a Static Map image to an Interactive Floorplan - PyCon SG 2019

Day 2 Opening Keynote - PyCon SG 2019

Demystifying RPA with Python - PyCon SG 2019

Demystifying Time Series Forecasting using Python - PyCon SG 2019

Digital process automation (RPA) using TagUI for Python - PyCon SG 2019

Ending Keynote - PyCon SG 2019

Faster Python apps with open source APM - PyCon SG 2019

Graylog : Centralized logging of Application Logs - PyCon SG 2019

How to build stream data pipeline with Apache Kafka and Spark Structured Streaming - PyCon SG 2019

How to train a wacky language model - PyCon SG 2019

Koalas: Pandas API on Apache Spark - PyCon SG 2019

Machine Learning Model Development and Operation in DBS - PyCon SG 2019

Opening Keynote - PyCon SG 2019

Python on AWS Lambda - PyCon SG 2019

Scaling product support with Python at WhatsApp - PyCon SG 2019

Stream Processing Fundamentals with Apache Beam - PyCon SG 2019

The curious case of slow/fast grequests code - PyCon SG 2019

Transfer Learning in Natural Language Processing (NLP) - PyCon SG 2019

Value Investing using Python and Panda - PyCon SG 2019

When life gives you Orange, make data speak volumes! - PyCon SG 2019

When Uncertainty Matters: Stochastic Programming for Inventory Model with Python - PyCon SG 2019

Charlas relámpago 2019-10-08

Ana Laura Diedrichs: Aprendizaje por refuerzo con OpenAI Gym | PyData Córdoba

Andres Pipicello: Sugerencias automáticas en sistemas conversacionales | PyData Córdoba

Carlos de la Torre: Del POC a producción - Infraestructura para machine-learning | PyData Córdoba

Carlos Gimenez: Data Science Best Practices con Kedro | PyData Córdoba

Daniel Imberman & Gonzalo Diaz: Data Products, From 0 to data science pipeline | PyData Córdoba

Erica Mason: Empowering Business to make model-based marketing decisions | PyData Córdoba

Federico Albanese: Machine Learning over graphs | PyData Córdoba

Georgina Flesia: Clustering data | PyData Córdoba

Gianmarco Cafferata & Francisco Lopez: Extracción de secciones de textos | PyData Córdoba

Gonzalo Barrera Borla: Optimización de ofertas, un enfoque dual | PyData Córdoba

Henrique Lopes: FKLearn, A functional machine learning library | PyData Córdoba

Ivana Seric: The evolution of basketball with data science | PyData Córdoba

Jorge Douglas: Pyplan a Graphical Programming Python IDE for creating Data Analytics Apps

Julian Eisenschlos: Know what you don't know, Tools to understand uncertainty in DL | PyData Córdoba

Junpeng Lao: A Hitchhiker's Guide to designing a Bayesian library in Python | PyData Córdoba

Junpeng Lao: Writing effective bayesian programs using TensorFlow and TFP | PyData Córdoba

Leandro Ferrado: Breaking the 80/20 dilemma in Data Science projects | PyData Córdoba

Marc Garcia: A better PyData ecosystem, one commit at a time | PyData Córdoba

Marc Garcia: Introducción a pandas (español) | PyData Córdoba

Milagro Teruel: Embeddings... embeddings everywhere | PyData Córdoba

Patricio Del Boca: Python ❤️Open Data! | PyData Córdoba

Paula Martinez & Rodrigo Beceiro: Computer Vision en la práctica | PyData Córdoba

Rodolfo Bonnin: A (Very Gentle) introduction to Quantum Computing | PyData Córdoba

Thierry Silbermann: Decentralized Machine Learning | PyData Córdoba

Lightning Talks, Day 3

Lightning Talks, Day 2

Lightning Talks, Day 1

02-106_LightningTark~Closing

01-106_lightning~closing

PYCON UK 2019 : Introduction

PYCON UK 2019 - Monday Lightning talks

PYCON UK 2019 - Sunday Introduction

PYCON UK 2019 Sunday Lightning talks

PyCon UK 2019 Saturday Introduction

PYCON UK 2019 - Saturday Lightning talks

PyCon UK 2019 Friday Introduction

PyCon UK 2019 Friday Lightning talks

Clausura PyCon Latam 2019 - Equipo Organizador

Lightning Talks / Charlas Relámpago - PyCon Latam 2019

Bienvenida PyCon Latam 2019

Videomemoria PyCon Latam 2019

"Build and hack your own IoT with MQTT" - Agnetha Korevaar (Kiwi Pycon X)

"Lightning Talks" - (Kiwi Pycon X)

"The Packaging Lifecycle with Poetry" - Clinton Roy (Kiwi Pycon X)

"Aircraft predictive maintenance using Python/ML" - Amar Verma (Kiwi Pycon X)

"Automate Your Integration Tests Using pytest-docker-compose" - Phoenix Zerin (Kiwi Pycon X)

"Building an interactive training environment using JupyterHub" - Graham Dumpleton (Kiwi Pycon X)

"From Pascal to Python" - Steve Dunford (Kiwi Pycon X)

"Getting started with MicroPython on a microcontroller" - Glenn Ramsey (Kiwi Pycon X)

"How to Write Python Code Others Like to Use" - Anna Tisch (Kiwi Pycon X)

"I'm So Meta Even This Acronym..." - Curtis Maloney (Kiwi Pycon X)

"Keynote: From NASA to Startups to Big Commerce" - Daniel Roy Greenfeld (Kiwi Pycon X)

"Keynote: The Natural State Of Computers" - Amber Brown (Kiwi Pycon X)

"Parallelism in Python" - Rounak Vyas (Kiwi Pycon X)

"Python: A Medley of Programming Paradigms" - Simon Merrick (Kiwi Pycon X)

"Python for Public Transport" - Alex Raichev (Kiwi Pycon X)

"Python product dev tools for electronics" - Barrie Duncan (Kiwi Pycon X)

"Python, Threads & Qt: Boom!" - Teijo Holzer (Kiwi Pycon X)

The journey of building a production-ready managed Kubernetes service

"Turning 'wat' into 'why'" - Katie McLaughlin (Kiwi Pycon X)

Using Python, Django, and ruthlessness to protect people from social media harassment.

Conference Close

Sunday Lightning Talks

Saturday Lightning Talks

Day 2 SciPy Tools Plenary Session

Day 3 Lightning Talks

Day 3 SciPy Tools Plenary Session

Closing Session

Day 2 Lightning Talks

Sprint Orientation

Lightning Talks 2019-07-11

SciPy Tools Plenary Session

Opening Session

Recruiting Session

GeoPython 2019 (June 25) Track 1

GeoPython 2019 (June 26) Track 1

GeoPython 2019 (June 26) Track 2

GeoPython 2019 (June 26) Track 2-2

GeoPython 2019 (June 25) Track 2

PyCon CZ Ostrava 2019 DAY 2 - BALLROOM - Live Stream

PyCon CZ Ostrava 2019 DAY 2 - CLUB - Live Stream

PyCon CZ Ostrava 2019 DAY 1 - BALLROOM - Live Stream

PyCon CZ Ostrava 2019 DAY 1 - CLUB - Live Stream

Lightning Talks

Alex Martelli - Ask Me Anything

PyConX Conference Goodbye

PyConX Conference Welcome and Introduction

Intro to SciPy Japan 2019: Scientific Python Conference

DjangoCon 2019 - Day 3 Lightning Talks

DjangoCon 2019 - Day 2 Lightning Talks

djangocon.close()

DjangoCon 2019 - Day 1 Lightning Talks

How PyLadies Brazil became the biggest PyLadies chapter of the world

Building Docs like Code: Continuous Integration for Documentation

Epigrammatic Python

Why Good Developers Write Bad Tests

10 Years In Industry as a Minority Developer

Cloud Made Simple with Serverless Python

CUDA in your Python: Effective Parallel Programming on the GPU

Egad! How Do We Start Writing (Better) Tests?

Free yourself from your ORM with mypy!

Intentional Deployment: Best Practices for Feature Flag Management

Introduction to Exploratory Data Analysis with the Sci-Analysis Python Package

Keynote: My Path to Becoming a Python Core Developer

Keynote: The Zen of Python Teams

Lightning Talks

Machine Learning by Example

Making Games With PPB

Serverless Python: All Vapor or Are There Benefits?

Solving the "no internet" problem in Botswana

Take Back the Web with GraphQL

Testing from the Ground Up

To comment or not? A data-driven look at developer attitudes toward code comments

When Booleans Are Not Enough... State Machines?

Djangocon 2019 - Europe - Day 3

Djangocon 2019 - Europe - Day 2

Djangocon 2019 - Europe - Day 1

А что, если без Python? Julia для машинного обучения и вообще / Глеб Ивашкевич

Что делать, если ваш код на Python тормозит / Григорий Бакунов (Яндекс)

Micropython для квестов в реальности и аркадных игр / Никита Левонович (КВЕСТОДЕЛЫ)

Убивай мутантов, спаси свой код / Никита Соболев (wemake.services)

Укрощая зверя: legacy-код, тесты и вы / Кирилл Борисов (Booking.com)

Видеоотчет о Moscow Python Conf ++ 2019

PyCon SK 2019 - Aula Magna - Nedela

PyCon SK 2019 - Aula Magna - Sobota

PyCon SK 2019 - Aula Minor - Sobota

PyCon SK 2019 piatok - Aula Minor (Aula Minor)

Алексей Борисенко - Сетевая программируемость с использованием Python [Ua]

Anton Caceres - The epic zoo of microservices [UA]

Christian Barra - Not just a Developer [En]

Елена Шилко - MQTT - прямая дорога в Интернет вещей [Ru]

Emanuil Tolev - Advanced, free, open-source application performance...

Gabriel Bianconi - Introduction to Face Processing with Computer Vision [En]

Jorge Torres - Machine Learning Democratization with Python [En]

Михаил Фарапонов - Overview of Kubernetes Metacontrollers with Python [Ru]

Тарас Мацик - Event Driven ML [UA]

Всеволод Соловьёв - Data science з печі до столу [Ru]

Pycon APAC 2019 - Anthony Khong - Property Based Testing in Python with Hypothesis

PyCon APAC 2019 - Aravind Putrevu - Faster Python apps with open source APM

PyCon APAC 2019 - Ardie Orden - Using Artificial Intelligence and Satellite Imagery

Pycon APAC 2019 - Argeo Tuble Alecha - Data Science and Machine Learning with Python

Pycon APAC 2019 Beng Keat Liew - PyCon APAC - Back to the Future!

Pycon APAC 2019 - Dmitry Trofimov - Best tools for Jupyter notebooks

Pycon APAC 2019 - Doni Rubiagatra - Turn your Flask App into Async using Quart

PyCon APAC 2019 - Gyenn Neil Ibo - Multi-lingual Text Data for Sentiment Classification

Pycon APAC 2019 - Jacob Kaplan-Moss - Interviewing as a Python engineer

Pycon APAC 2019 - Li Ting Chen - Python’s role in accelerating biomedical science

Pycon APAC 2019 - Lightning Talks Part 1

Pycon APAC 2019 - Lightning Talks Part 2

Pycon APAC 2019 - Lightning Talks Part 3

PyCon APAC 2019 - Marte Soliza - Using Asyncio in Python 3

PyCon APAC 2019 - Narendran - Empathy Maketh an Engineer

PyCon APAC 2019 - Phillip Espina - Python's AI/ML for the Crypto-Industry

Pycon APAC 2019 - Suzy Lee - How did you know? Explaining Black Box Model Predictions in Python

Pycon APAC 2019 - Taihsiang Ho - Homemade scientific clusters in Python

Pycon APAC 2019 - Takanori Suzuki - Automate the Boring Stuff with Slackbot

Pycon APAC 2019 - Tom Dyson - Here Come The Robots - Python and Machine Learning

Pycon APAC 2019 - Yohei Onishi - Building Analytics Workflow using Airflow and Spark

Aftermovie 2019 - Pycon Colombia 2019

Álvaro Justen - Brasil.IO: liberation of public data with Python - PyCon Colombia 2019

Andres Giraldo Carvajal - Interactive Data Visualization in Python - PyCon Colombia 2019

Arkadiusz Adamski - Automating banner generation using Python - PyCon Colombia 2019

Benjamin Lewis - Keynote Speaker Conference - PyCon Colombia 2019

Benjamin Lewis - PyCon Colombia 2019

Camilo Sepulveda - PyCon Colombia 2019

Carlos Miguel Patiño - Introduction to Generative Adversarial Networks - PyCon Colombia 2019

Carol Willing - Keynote Speaker Conference - PyCon Colombia 2019

Carol Willing - PyCon Colombia 2019

Carolina Gomez - Automation of tasks with selenium - PyCon Colombia 2019

Cristina Gomez - Compressed sensing for indoor radiolocalization in python - PyCon Colombia 2019

David Cardozo - Deep learning for autonomous vehicles, case: Kiwibot - PyCon Colombia 2019

David Delgado Ruiz - Story of an junior engineer - PyCon Colombia 2019

Diego Camilo Peña - IOT and hardware interaction with Python - PyCon Colombia 2019

Eduardo Ismael Garcia - Creating a BlockChain with Python - PyCon Colombia 2019

Felipe Hoffa - What can we learn from 42 TB of code? - PyCon Colombia 2019

Gabriele Tani - How to recover hidden information to improve job post matching - PyCon Colombia 2019

Gonzalo Peña - The state of the Anaconda - PyCon Colombia 2019

Gonzalo Quiroga - IGNIS - PyCon Colombia 2019

Interview Benjamin Lewis - Keynote Speaker - PyCon Colombia 2019

Interview Carol Willing - Keynote Speaker - PyCon Colombia 2019

Interview Jake Vanderplass - Keynote Speaker - PyCon Colombia 2019

Interview Jessica Mckellar - Keynote Speaker - PyCon Colombia 2019

Interview Jorge Vergara - CTO at IBM Colombia - PyCon Colombia 2019

Interview Julián Amaya - CEO at Monoku - PyCon Colombia 2019

Interview Kian Katanforoosh - Keynote Speaker - PyCon Colombia 2019

Interview Ola Sendecka - Keynote Speaker - PyCon Colombia 2019

Interview Russel Keith Magee - Keynote Speaker - PyCon Colombia 2019

Ivan Lozano - Using a Drone to identify and rescue people - PyCon Colombia 2019

Ivan Torroledo - Building next generation writers using AI - PyCon Colombia 2019

Jake Vanderplas - Keynote Speaker Conference - PyCon Colombia 2019

Javier Daza Comas - Creating succesfull tech communities - Pycon Colombia 2019

Jessica Mckellar - Keynote Speaker Conference - PyCon Colombia 2019

Johana Salinas Quintana - How to become a Data Science Superhero? - PyCon Colombia 2019

Jorge Gonzalez - Real driving data to improve road safety in bogota - PyCon Colombia 2019

Jorge Luis Galvis - Going serverless with python - PyCon Colombia 2019

Jorge Martinez - An artistic neural style algorithm - PyCon Colombia 2019

Jose Giraldo - Deep learning music - PyCon Colombia 2019

Juan Manuel Álvarez - Truth is always strange - Fuzzy logic in Python - PyCon Colombia 2019

Kian Katanforoosh - Keynote Speaker Conference - PyCon Colombia 2019

Kian Katanforoosh - PyCon Colombia 2019

Luis David Camacho - High Perfomance Pandas - PyCon Colombia 2019

Mario Sergio - How we face the challenges of maintaining an inclusive community in Brazil

Matt Harrison - Consulting for Introverted Developers - PyCon Colombia 2019

Nick Sweeting - Database Integrity in Django - PyCon Colombia 2019

Ola Sendecka - Keynote Speaker Conference - PyCon Colombia 2019

Ola Sendecka - PyCon Colombia 2019

PyCon Colombia 2019 promo

Roman Prykhodchenko - Load distribution in heterogeneous microservice environments - PyCon 2019

Russell Keith-Magee - Keynote Speaker Conference - PyCon Colombia 2019

Russell Keith-Magee - PyCon Colombia 2019

William Gomez Ortega - AUREAS: A tool for unsupervised species call recognition - PyCon Colombia

A developer amongst (data) journalists by Eléonore Mayola

Binding the Sea by Åke Forslund

Build your own event loop by Pradip Caulagi

Closing keynote by Adam Tornhill

Designing an intuitive framework for complex pipelines in PySpark by Sebastian Ånerud

Digging MUD in Python by Samuel Regandell

Gait phase recognition using machine learning algorithm with IMU sensors by Binbin Su

Mantra - A Deep Learning Development Kit by Ross Taylor

Opening keynote by Lorena Mesa - Now is better than Never...

PyCon Sweden 2018 - lightning talks part 1

PyCon Sweden 2018 - lightning talks part 2

PyCon Sweden 2018 - lightning talks part 3

PyCon Sweden 2018 opening by chairwoman Anna K. Lindegren

Charlas Rápidas. 2018-11-24 Sábado (Mañana)

Charlas Rápidas. 2018-11-24 Sábado (Tarde)

Charlas Rápidas. 2018-11-24 Viernes

Deploying Django App On AWS Lambda

A deep revolution in speech processing and analysis - Pawel Cyrta

AI meets Art - Agata Chęcińska

Application of Recurrent Neural Networks to innovative drug design - Rafał A. Bachorz

Bit to Qubit: Data in the age of quantum computers - Shahnawaz Ahmed

Can you enhance that? Single Image Super Resolution - Katarzyna Kańska

Can you trust neural networks? - Mateusz Opala

Comixify: Turning videos into comics - Adam Svystun, Maciej Pęśko, Tomasz Trzcinski

Computer vision challenges in drug discovery - Maciej Hermanowicz

Conference Opening Notes

Data Pipeline Hyperparameter Optimization - Politechnika Poznanska

Deep Learning Semantic Segmentation for Nucleus Detection - Dawid Rymarczyk

Distributed deep learning and why you may not need it - Jakub Sanojca, Mikuláš Zelinka

From Data to Deliverable - Steph Samson

Hand in hand with weak supervision using snorkel - Szymon Wojciechowski

High Performance Data Processing in Python - Donald Whyte

Hitting the gym: controlling traffic with Reinforcement Learning - Steven Nooijen

How I learnt computer vision by playing pool - Łukasz Kopeć

In Browser AI - neural networks for everyone - Kamila Stepniowska, Piotr Migdał

It is never too much: training deep learning models with more than one modality - Adam Słucki

Keynote - Aleksandra Przegalińska

Keynote - Lynn Cherny

Keynote - Stefania Druga - "Cognimates: Read, Write and Tinker with AI"

Keynote: The Neural Aesthetic - Gene Kogan

Learning to rank @ allegro.pl - Tomasz Bartczak, Ireneusz Gawlik

Predicting preterm birth with convolutional neural nets - Tomasz Włodarczyk, Szymon Płotka

PyTorch 1.0: now and in the future - Adam Paszke

Recognizing products from raw text descriptions using... - Tymoteusz Wołodźko, Tomasz Płomiński

Similarity learning using deep neural networks - Jacek Komorowski

Spammers vs. Data: My everyday fight - Juan De Dios Santos

Spot the difference: train your image analytics model to recognize fine grain...- Katarina Milosevic

Step by step face swap - Sylwester Brzęczkowski

The Dawn of Mind Reading in Python - Krzysztof Kotowski

The smart shopping basket: A Case Study with deep..- Marcin Stachowiak, Michal Dura, Piotr Szajowski

Uncertainty estimation and Bayesian Neural Networks - Marcin Możejko

Visualize, Explore and Explain Predictive ML Models - Przemyslaw Biecek

Accelerating Data Science with RAPIDS - Keith Kraus

Approaching AI in Banking - Hussain Sultan

Avoiding Bad Database Surprises: Simulation and Scalability - Steven Lott

Beautiful, Interactive, and Portable Maps using Folium and Live API Data - Ariel M'ndange-Pfupfu

Building a Machine Learning Enabled Bot in the Cloud - Jerry Hargrove

Cleaning and Tidying Data in Pandas - Daniel Chen

Dash: data exploration web apps in pure Python - Chelsea Douglas

Data visualization with plotly py: Version 3 and beyond - Jon Mease

Democratizing NLP content modeling with transfer learning using GPUs - Sanghamitra Deb

Developing Dashboard Applications using Bokeh - Luke Canavan

Dimensionally reducing data squeezing out the good stuff - Aabir Abubaker Kar

Do Your Homework! Writing tests for Data Science and Stochastic Code - David Waterman

End to End Machine learning pipelines for Python driven organizations - Nick Harvey

Five Kinds of Python Functions - Steven Lott

Going beyond “Sorry, I didn’t get that” building AI assistants that scale... - Justina Petraitytė

Graphs: Datastructures to Query - Benjamin Ortiz Ulloa

Inside Out - Creating a Python Ecosystem for Analysis and Better Government - Babila Lima

Intake - taking the pain out of data access - Martin Durant

Keynote: A Sailor's View of Python And the idea of "Defensive Programming" - Steven Lott

Keynote: Learning from Machines - Ashi Krishnan

Keynote: The Business of Open Source - Travis E. Oliphant

Keynote: Using Data Science to Recruit Data Scientists - Maryam Jahanshahi

Machine Learning in the age of increasing Data Privacy Consciousness - Sam Talasila

Making interactive visualizations easy, inside and outside of notebooks - Julia Signell

Measures and Mismeasures of Algorithmic Fairness - Manojit Nandi

Mining dockless bikeshare and dockless scootershare trip data - Stefanie Brodie, Kiana Roshan Zamir

Probabilistic Programming in the Real World - Zach Anglin

Recreating, Understanding, and Visualizing FiveThirtyEight's... - Matthew Brems and Joseph Nelson

RESTful Machine Learning with Flask and TensorFlow Serving - Carlo Mazzaferro

Right Code, Right Place, Right Time - Tim Hopper

Scaling PyData with Dask - Martin Durant and Jim Crist

Sell cron, buy Airflow: Modern data pipelines in finance - James Meickle

Single Page Apps: What an API Developer Should Know - Alison Rowland

Skein: a simpler way to deploy applications on Hadoop Clusters - Jim Crist

Skorch - A Union of Scikit-learn and PyTorch - Thomas Fan

Task Failed Successfully - Jeremiah Lowin

The First Notebook War - Martin Skarzynski

Tracking plasma flows at the solar surface with the Solar Dynamics Observatory - Raphael Attie

uarray - Efficient and Generic Array Computation - Travis E. Oliphant, Saul Shanabrook

Using Sockeye Neural Machine Translation in a Streaming Pipeline - Jeff Zemerick

Web Scraping with Beautiful Soup - Monica Puerto

Webscraping Responsibly for Social Science Research - Graham MacDonald

Why do you have to make it so complicated? - James Powell, Brandon Burroughs, Daniel Allan

Words in Space: A Visual Exploration of Distance, Documents, and Distributions... - Rebecca Bilbro

PyParis 2018 - Sponsor speech (Wifirst)

Pycon Ireland 2018: Adding the three pillars of Observibility to your Python app - Eoin Brazil

Pycon Ireland 2018: An Idiots Guide to (Open) Data Science - Andrew Bolster

Pycon Ireland 2018: Asynchronous programming in Python - Mikhail Medvedev

Pycon Ireland 2018: Building a Fine Grained Image Classification System- Fergal Walsh

Pycon Ireland 2018: Django APIs, Versioning and You - Rebecca Martin

Pycon Ireland 2018: Functional Programming for Data Science - Neal Ó Riain

Pycon Ireland 2018: High Performance Data Processing in Python - Donald Whyte

Pycon Ireland 2018: Keynote: Coding for Pleasure - Miguel Grinberg

PyCon Ireland 2018: Keynote: Python in Education - Dr. Brett Becker & Keith Quille

Pycon Ireland 2018: Leaving Certificate Computer Science & Python - Stephen Murphy

Pycon Ireland 2018: Machine Translation with Keras - Bojan Bozic

PyCon Ireland 2018: More Than You Ever Wanted To Know About Python Functions - Mark Smith

Pycon Ireland 2018: Patient Data Made Real - Lorenzo Trojan

Pycon Ireland 2018: Powering up your Python web applications - Allyn Hunt

Pycon Ireland 2018: Prediction of risk factors for stroke - Olga Lyashevska

Pycon Ireland 2018: Profiling: Find the Squeaky Wheel - Nick Timkovich

Pycon Ireland 2018: Programming by poking: some experiences in teaching with Python - Ben Fagan

PyCon Ireland 2018: Publish a (Perfect) Python Package on PyPI - Mark Smith

Pycon Ireland 2018: Python as a tool for research - Dr Suzanne Little

PyCon Ireland 2018: Python on Windows is Okay, Actually -Steve Dower

PyCon Ireland 2018: Recruitment Session

Pycon Ireland 2018: Testing python security - Jose Manuel Ortega

Pycon Ireland 2018: Visualisation in Python - Shane Lynn

PyCon Ireland 2018: What is new in Python 3.7? - Stephane Wirtel

[ENG] Alexander Todorov: "How to write pylint plugins" / #PiterPy

[ENG] Аnton Shalimov: "Aviasales. A look under the hood. Tornado based search engine." / #PiterPy

[ENG] Artem Malyshev: "Readability matters" / #PiterPy

[ENG] Denis Kataev: "Python and binary data" / #PiterPy

[ENG] Dmitry Dygalo: "Testable code: making the (testing) world better" / #PiterPy

[ENG] Dmitry Karpov: "Real-time apps with Python. Tips and tricks" / #PiterPy

[ENG] Dmitry Nazarov: "EdgeDB workshop" / #PiterPy

[ENG] Jonas Obrist: "Artisanal Async Adventures" / #PiterPy

[ENG] Juan Luis Cano: "Catch that asteroid with poliastro!" / #PiterPy

[ENG] Konstantin Ignatov: "Python application monitoring: let's do it logging style" / #PiterPy

[ENG] Lena Volzhina: "How to combine physical models, ML and production performance" / #PiterPy

[ENG] Lynn Root: "asyncio in Practice: We Did It Wrong" / #PiterPy

[ENG] Mario Corchero: "Effortless Logging: A deep dive into the logging module" / #PiterPy

[ENG] Michal Karzynski: "Developing elegant workflows with Apache Airflow" / #PiterPy

[ENG] Miroslav Šedivý: "A Day Has Only 24±1 Hours: import pytz" / #PiterPy

[ENG] Panel discussion: The Future of Python / #PiterPy

[ENG] Pascal van Kooten: "High-Frequency Cryptocurrency Trading using Asyncio" / #PiterPy

[ENG] Piotr Migdal: "Learning neural networks within Jupyter Notebook" / #PiterPy

[RUS] Alexander Todorov: "How to write pylint plugins" / #PiterPy

[RUS] Аnton Shalimov: "Aviasales. A look under the hood. Tornado based search engine." / #PiterPy

[RUS] Artem Malyshev: "Readability matters" / #PiterPy

[RUS] Denis Kataev: "Python and binary data" / #PiterPy

[RUS] Dmitry Dygalo: "Testable code: making the (testing) world better" / #PiterPy

[RUS] Dmitry Karpov: "Real-time apps with Python. Tips and tricks" / #PiterPy

[RUS] Dmitry Nazarov: "EdgeDB workshop" / #PiterPy

[RUS] Jonas Obrist: "Artisanal Async Adventures" / #PiterPy

[RUS] Juan Luis Cano: "Catch that asteroid with poliastro!" / #PiterPy

[RUS] Konstantin Ignatov: "Python application monitoring: let's do it logging style" / #PiterPy

[RUS] Lena Volzhina: "How to combine physical models, ML and production performance" / #PiterPy

[RUS] Lynn Root: "asyncio in Practice: We Did It Wrong" / #PiterPy

[RUS] Mario Corchero: "Effortless Logging: A deep dive into the logging module" / #PiterPy

[RUS] Michal Karzynski: "Developing elegant workflows with Apache Airflow" / #PiterPy

[RUS] Miroslav Šedivý: "A Day Has Only 24±1 Hours: import pytz" / #PiterPy

[RUS] Panel discussion: The Future of Python / #PiterPy

[RUS] Pascal van Kooten: "High-Frequency Cryptocurrency Trading using Asyncio" / #PiterPy

[RUS] Piotr Migdal: "Learning neural networks within Jupyter Notebook" / #PiterPy

50 оттенков celery / Олег Чуркин (TechOps)

A Hacker's Guide to Securing Python Web Applications / Eyitemi Egbejule (NaijaSecForce)

Beyond jupyter / Андрей Попов (Positive Technologies)

Dark Python: Social engineering and hacking with 70% success rate / Lukas Hurych (Twisto.cz)

Django under microscope / Артем Малышев (Self Employed)

Эффективное использование Jupyter и PySpark на Hadoop / Павел Тарасов (ЦИАН)

High Performance Data Processing in Python / Donald Whyte (Engineers Gate)

Интерактивный и холиварный доклад про линтеры / Никита Соболев (wemake.services)

Как обновить Python 2.7 до Python 3.6 и не умереть / Александр Полищук (Код Безопасности)

Как учить людей программированию и радоваться жизни / Илья Лебедев (devman.org)

Как выкинуть из проекта C++ код, чтобы за это ничего не было / Александр Боргардт

Как защитить алгоритм машинного обучения от Adversarial-примеров / Сергей Дудоров (Digital Security)

Хорошие и плохие практики для написания тестируемого кода / Дмитрий Дыгало (kiwi.com)

Make Python fast again / Ефрем Матосян (Positive Technologies)

Мастер-класс "Эффективная Selenium-инфраструктура" / Иван Крутов (Aerokube)

Опыт использования Apache Kafka в World of Tanks / Левон Авакян (Wargaming)

Открытие Moscow Python Conf++ 2018

Pylint изнутри. Как он это делает / Максим Мазаев (ЦИАН)

Python Virtual Assistant, или Как собрать бота с AI на простом стеке / Олег Пличко

Распространенные ошибки в архитектуре Django-приложений / Алексей Половинкин (Agima)

Refactoring in Python: design patterns and approaches / Tin Marković (Kiwi.com)

Система ML-моделирования финансовых показателей / Олег Мангутов (Deloitte Analytics Insitute)

Создание DSL-компиляторов на Python / Пётр Советов (МИРЭА)

Theory of Neural Networks / Beau Carnes (freeCodeCamp.org)

Ускорение SQLAlchemy для архитектурных космонавтов / Алексей Старков (Qrator Labs)

Видеоотчет о Moscow Python Conf++ 2018

Wagtail: когда хочется чего-то приятнее, чем просто Django / Игорь Мосягин (Lamoda)

Запись трансляции Moscow Python Conf++ 2018. 22 окт, зал "Большой"

Запись трансляции Moscow Python Conf++ 2018. 22 окт, зал "Малый"

Запись трансляции Moscow Python Conf++ 2018. 23 окт, зал "Большой"

Запись трансляции Moscow Python Conf++ 2018. 23 окт, зал "Малый"

Запускаем Python-приложение в облака / Евгений Слезко (Marilyn)

PyData.tokyo One-day Conference 2018 Session1

PyData.tokyo One-day Conference 2018 Session2

PyData.tokyo One-day Conference 2018 Session3

PyData.tokyo One-day Conference 2018 Session4

PyData.tokyo One-day Conference 2018 Session5

PyData.tokyo One-day Conference 2018 Session6

PyData.tokyo One-day Conference 2018 Sponsor Session

Keynote - Painel sobre dados abertos e tecnologias cívicas

2nd Keynote by Sidu Ponnapa

3rd Keynote By Travis Oliphant

4th Keynote by Carol Willing

Adventures in iterations By Vikrant Patil

Alexa enabled smart home programming with Python By Sonal Raj

Amazing world of animation - powered by python By Sreenivas Alapati

AQR Quant De-Mystified By Navraj Bhardwaj

Automating testbed experiments, data collection and visualization with Python By Sunit Kumar Nandi

Bayesian A/B testing using Python By Vaibhav Pawar

Building better Python microservices using GRPC By Narendran R

Cleaning data with Python By Anand S

Creating 3rd generation Web APIs using Hydra and Hydrus By Akshay Dahiya

Deploying a Python web app onto a Kubernetes Cluster By Tarun Pothulapati

Django on day 500 By Amit Singh Sethi

Executing scripts in a few milliseconds with MicroPython By Marwan Al-Sabbagh

Experience with Python type hints By Kracekumar Ramaraju

FOSSASIA Community Talk By Mario Behling

Handling DASH streams - Generation, Consumption & Clipping By Arnav

How Helpshift built machine learning platform using Python at large scale By Shyam Shinde

Inside the World's Largest Python Course on Coursera By Charles Severance

Language Model (Text Analysis) using Python from scratch By Divya Choudhary

Large scale web crawling using Python By Anand B Pillai and Noufal Ibrahim

Learn Guitar Via Python Programming (MIDI Parsing) By Rishabh Shah and Srinivas Kalyani

[Lightning Talk] At the eye of the flood by Biswaz

Lightning Talk by DBS

Lightning Talk by Enfa Rose George

Lightning Talk by Marc Garcia

Lightning Talk by Yuktesh Chintamadaka (IBM)

[Lightning Talk] Climbing the Minesweeper Leaderboards by Samarth Hattangady

[Lightning Talk] Cool features of Python 3.7 by Jaysinh Shukla

[Lightning Talk] EEG Controlled Rover - A Brain-Computer Interface by Prajwal and Venkatesh

[Lightning Talk] Failure of the Tests

[Lightning Talk] i-Tagger by Pramati

[Lightning Talk] Machine Learning and AI for the Greater Good by Praveen Pankajakshan (Corteva)

[Lightning Talk] Micropython - Python for embedded Systems by Kalpit Champanery

[Lightning Talk] Python: Batteries Included. Now Bulletproof too by Soroco

[Lightning Talk] Smart Drowsiness Detection System using Deep Learning by Sai Amrit Patnaik

[Lightning Talk] Using ChainMaps to simplify CLI argument parsing by Govind

[Lightning Talk] Using Regular Expressions for parsing Indian Addresses by Yash Chilgupakar

[Lightning Talks] Leveraging Communities by Lakshya Sivaramakrishnan

Managing flood risk in this modern age By Arijit Saha and Atul Singh

Metaclasses and decorators: a match made in space By Ishan Srivastava

Optimizations in Web Development by Megha Sharma

Processing videos effectively By R S Nikhil Krishna and Lokesh Kumar T

PyCon India 2018 Opening Video by Ramesht Shukla

Pyflyby: Automatic imports for Python By Karl Chen

Python Project Workflows - Continuous Deployment Friendly By Abhijit Gadgil

Satellite Image Processing with Python By Shubham Sharma

Speed up your Python modules using Rust By Abhiram Ravikumar

Sponsor Talk - Indeed By Subhas KS and Yosef Wehby

Testing micro-services made easy By Devi A S L

The art of effective visualization of multi-dimensional data - Dipanjan Sarkar

The Growth of the Python Community in Africa By Marlene Mhangami

Understanding Caching in Python By Chirag Shah

Using Jupyter to Empower the Less Technical By Marc Udoff and Sriram Nagarajan

Using NLP to demystify 'Terms and Conditions' and summarize the contents By Aroma Rodrigues

VIDEO RESUMEN PYCONES 2018

Vote of Thanks - PyCon Team

What you need to know about data classes in Python 3.7 By Sasidhar Donaparthi

Adam Jurkiewicz - Python in schools in Poland - PyCode Conference 2018

Agata Skamruk & team - Thanks to sponsors and partners

Filip Szamborski - Czy Python umie latać? - PyCode Conference 2018

Kaja Milanowska - Artificial Intelligence in everyday medical practice - PyCode Conference 2018

Łucja Świetlińska i Dagmara Korusiewicz - Dlaczego Scrum nie działa - PyCode Conference 2018

Maciej Januszewski - AI w służbie zdrowia - Maciej Januszewski

Małgorzata Niewiem - GeoPython - how to save the world using Python - PyCode Conference 2018

Marcin Jaroszewski - Entliczek, pętliczek - Enum, czyli wyliczanki... - PyCode Conference 2018

Merixstudio - rozstrzygnięcie konkursu - PyCode Conference 2018

Michał Dżaman - Going big with Django - profiling, optimization and scaling - PyCode Conference 2018

Michał Jadczuk - Using convolutional neural networks to analyze - PyCode Conference 2018

Michał Wysokiński - AsyncIO in production - War Stories - PyCode Conference 2018

Mikaeil Orfanian - Design and Architecture in Every Day Programming - PyCode Conference 2018

Miłosz Kusiciel - Jak zwiekszyć wydajność w Django - PyCode Conference 2018

Pascal van Kooten - High-Frequency Cryptocurrency Trading using Asyncio - PyCode Conference 2018

Paweł Stoworowicz - Statyczne typowanie w Pythonie - type annotations & mypy -PyCode Conference 2018

Piotr Januszewski - Planning in Deep Reinforcement Learning - PyCode Conference 2018

Wojciech Barczyński - Effective CD for your platform with Kubernetes - PyCode Conference 2018

Wojciech Barczyński - How to monitor your micro-service with Prometheus? - PyCode Conference 2018

01-204_From Data to Web Application: Anime Character Image Recognition with...(Iskandar Setiadi)

01-205_Django を Zappaで構築してServerless Python のベストプラクティスを探る(向山 裕介/Yusuke Mukoyama)

01-206_Day2_Lightning Talk~Closing

02-204_1次元畳み込みフィルターを利用した音楽データのオートエンコーダ(新倉 涼太)

03-204_Pythonによる異常検知入門(大山匠)

03-205_料理写真が美味しく撮れる！ 開発現場から覗くAI料理カメラの裏側(森永雄也)

04-205_Pythonで始めるウェブスクレイピング実践入門(田中 慎太郎)

05-203_Python研修の作り方-Teaching Is Learning-(Yusuke Nishio)

05-204_Pythonで「お絵描きパズル」を解いてみた。(小栗　潤一)

06-204_Python, AWS and FinTech(Pavlos Christoforou)

07-204_C拡張と共に乗り切るPython 2→3移行術(末田卓巳)

07-205_AltJSとしてのPython - フロントエンドをPythonで書こう(長谷場 潤也)

01-101_実践・競馬データサイエンス(貫井 駿)

01-103_Pythonで時系列のデータを分析してみよう(Tatsuya Kobayashi)

01-104_Pythonistaの選球眼(せんきゅうがん) - エンジニアリングと野球の目利きになる技術(Shinichi NAKAGAWA(野球エンジニア))

01-105_Day1_Lightning Talk~Closing

01-201_Integrate Full-text Search service with Django(池内 孝啓 / Takahiro Ethan Ikeuchi)

01-202_JVM上で動くPython3処理系cafebabepyの実装詳解(澁谷 典明/Yoshiaki Shibutani)

01-203_複数アプリケーションのプロセスとログを管理するための新しいツールと手法(谷津真樹/Masaki Yatsu)

02-101_Why you should care about types: Python Typing in the Facebook Backend(Luka Sterbic)

02-102_オンザフライ高速化パッケージの比較：Numba, TensorFlow, Dask, etc(Yukio Okuda)

02-103_Fun with Python and Kanji(Michael Penkov)

02-104_Introduce syntax and history of Python from 2.4 to 3.7(Manabu TERADA)

02-201_Migrating from Py2 application to Py3: first trial in MonotaRO / Python2 から Python3 へ...(増田泰)

02-202_Sphinx-2.0 とドキュメントの未来(Takeshi KOMIYA)

02-203_Make a Drone using RaspberryPi and Google VoiceKit by Python(片寄 里菜 / Lina Katayose)

03-101_Applying serverless architecture pattern to distributed data processing(Denys Makogon)

03-102_Django REST Framework におけるAPI実装プラクティス(芝田 将)

03-103_The Modern OAuth 2.0(Hsiaoming Yang)

03-104_Rust と Python(Hideo Hattori)

03-201_SymPyによる数式処理(Hayao Suzuki)

03-202_Djangoだってカンバンつくれるもん(Django Channels + Vue)_(denzow)

03-203_契約書データ関連のAI開発に伴う、前処理及び匿名化処理についての実例(本田勝寛)

04-101_Day1_Opening~Keynote_Argentina in Python: community, dreams,...(Kaufmann Manuel)

04-102_招待講演_東大松尾研流 実践的AI人材育成法(中山 浩太郎)

04-104_Webアプリケーションの仕組み(Takayuki Shimizukawa)

04-105_あなたと私いますぐパッケージン(Atsushi Odagiri)

04-107_Pythonで解く大学入試数学(新井 正貴)

04-201_Day2_Keynote_「Pythonでやってみた」：広がるプログラミングの愉しみ(磯 蘭水)

04-202_niconicoにおけるコンテンツレコメンドの取り組み(大元 司)

04-203_Djangoアプリケーションにおけるトイル撲滅戦記(Yasuaki Matsuda)

04-204_Artisanal Async Adventures(Jonas Obrist)

05-202_Pythonでざっくり学ぶUnixプロセス(tell-k)

06-101_DjangoではじめるPyCharm実践入門(Kashun Yoshida)

06-102_Pythonを使ったハードウェア開発について(北神雄太)

06-103_Interactive Network Visualization using Python 〜 NetworkX + BokehでPEPの参照関係を...(Tomoko Furuki)

06-202_REST API に疲れたあなたへ贈る GraphQL 入門(Tsukagoshi Keisuke)

06-203_WILDCAT SDKは量子コンピュータビジネスの味方となるのか！？(あべんべん)

07-101_PyCon JP における子ども向けワークショップの活動事例と実施の意義(Daisuke Saito)

07-102_Interpretable Machine Learning, making black box models explainable with Python!(David Low)

07-103_メルカリにおける AI 活用事例(千葉 竜介)

07-104_自分が欲しいものをPythonで書く方法(Python for Myself)(杉山　剛)

07-201_HomeSecurity with Python(Yuki Takino)

07-203_Notebook as Web API: Turn your notebook into Web API(横石和貴)

EuroSciPy 2018 SESSION Track 2 - Afternoon (Part 2) 31 08 2018

EuroSciPy 2018 SESSION TRACK 2 MORNING 31 08 2018

Friday 31 August - Track 1 - Afternoon (Part 1)

Friday 31 August - Track 1 - Afternoon (Part 2)

Friday 31 August - Track 1 - Morning

EuroSciPy 2018 SESSION TRACK 2 AFTERNOON PART 2 30 08 2018

EuroSciPy 2018 SESSION TRACK 2 AFTERNOON PART 30 08 2018

EuroSciPy 2018 SESSION TRACK 2 MORNING 30 08 2018

Thursday 30 August - KEYNOTE - How to drive business decisions with AI

Thursday 30 August - Track 1 - Afternoon (Part 1)

Thursday 30 August - Track 1 - Afternoon (Part 2)

Thursday 30 August - Track 1 - Morning

Deep Diving into GANs: From Theory to Production Michele De Simoni, Paolo Galeone 29 08 2018

Deep Learning in Python using Chainer, C. Loomis 29 08 2018

EuroSciPy Advanced Session - CFFI, Ctypes, Cython: the Good, the Bad and the Ugly

EuroSciPy Advanced Session - Data visualization: from default to efficient

EuroSciPy Advanced Session - Parallel Data Analysis with Dask

EuroSciPy Advanced Session - The Hitchhiker's Guide to Parallelism with Python

EuroSciPy Applications Session Advanced machine learning, Y. Peleg 29 08 2018

EuroSciPy Applications Session Advanced Understanding and diagnosing your machine-learning29 08 2018

EuroSciPy 2017: Advanced Pandas

EuroSciPy 2017: AMfe - Finite Elements for Structural Dynamics with Simplicity in Mind

EuroSciPy 2017: Arcas - Using Python to access open research literature

EuroSciPy 2017: Autoscaling distributed compute with Dask, Kubernetes and AWS

EuroSciPy 2017: AutoWIG: Wrapping very large C++ libraries in Python automatically

EuroSciPy 2017: Bayesian Optimization - Can you do better than randomly guessing parameters?

EuroSciPy 2017: Cython

EuroSciPy 2017: Deep Learning for Fraud Detection

EuroSciPy 2017: fastmat - A simple Package for Fast Linear Transforms

EuroSciPy 2017: FluRS - A Library for Streaming Recommendation Algorithms

EuroSciPy 2017: Fully Convolutional Networks for Image Segmentation

EuroSciPy 2017: GeoPandas - geospatial data in Python made easy

EuroSciPy 2017: Getting the hang of WASM

EuroSciPy 2017: Git

EuroSciPy 2017: Handshakes, Citizen Science and Evolution

EuroSciPy 2017: Interactive 3D Visualization in Jupyter Notebooks

EuroSciPy 2017: Introduction into the ppci project

EuroSciPy 2017: Keras

EuroSciPy 2017: Keynote: How to Fix a Scientific Culture: Psychology as a Cautionary Tale

EuroSciPy 2017: Keynote: PyTorch: Framework for fast, dynamic deep learning and scientific computing

EuroSciPy 2017: Leverage knowledge from under-represented classes in machine learning

EuroSciPy 2017: Lightning Talks

EuroSciPy 2017: Matplotlib

EuroSciPy 2017: nbval - Testing your notebooks

EuroSciPy 2017: NetworkX

EuroSciPy 2017: NumPy (1/2)

EuroSciPy 2017: NumPy (2/2)

EuroSciPy 2017: Pandas

EuroSciPy 2017: Poster Introductions

EuroSciPy 2017: Pyrate - Optical Raytracing Based on Python

EuroSciPy 2017: Python (1/2)

EuroSciPy 2017: Python (2/2)

EuroSciPy 2017: Real-time Crowd-sourced Detection of Earthquakes

EuroSciPy 2017: Scikit-image

EuroSciPy 2017: Scikit-learn (1/2)

EuroSciPy 2017: Scikit-learn (2/2)

EuroSciPy 2017: SciPy

EuroSciPy 2017: Simphony-Remote - Accessing containerized desktop and web apps with a browser

EuroSciPy 2017: SymPy

EuroSciPy 2017: Testing the unknown: how to test scientific codes

EuroSciPy 2017: The OpenTURNS uncertainty quantification Python module

EuroSciPy 2017: Tricks for Efficient Multicore Computing

EuroSciPy 2017: Working with Audio Data in Python

EuroSciPy Advanced Session

EuroSciPy Advanced Session - A tour of Python profiling and optimization

EuroSciPy Advanced Session - Privacy for Data Scientists

EuroSciPy Applications Session

EuroSciPy Applications Session Handling Geospatial Data using Python, Part II

Friday 31 August - KEYNOTE - Python in medicine: processing, learning and visualization of data

Live stream di EuroSciPy Session 1

Live stream di EuroSciPy Session 1b

Live stream EusoSciPy2018 session 2

Live stream EusoSciPy2018 session 2b

Conference Close

Democratizing Data Tracy Teal (The Carpentries)

Disease Prediction Using the World's Largest Clinical Lab Dataset Cristian Capdevila (Prognos)

The Reporter's Notebook - Mark Hansen (Columbia Journalism School)

Why Contribute to Open Source? - Julia Meinweld (Two Sigma Investments)

Beyond Interactive: Scaling Impact with Notebooks at Netflix - Michelle Ufford (Netflix)

Binder: Lowering the bar to sharing interactive software- Tim Head (Wild Tree Tech)

Business Summit roundtable: The current environment

Canadians land on Jupyter - Ian Allison, James Colliander

Charles Smith (Netflix) interviewed at JupyterCon NY 2018

Containerizing notebooks for serverless execution (sponsored by AWS)

Current RISE capabilities and its evolution into the future- Damián Avila (Anaconda, Inc.)

Dan Mbanga (AWS) interviewed at JupyterCon NY 2018

Data Science as a Catalyst for Scientific Discovery Michelle Gill, Ph.D. (BenevolentAI)

Data science in US and Canadian higher education- Laura Noren (Obsidian Security)

Designing for interaction- Scott Sanderson (Quantopian)

Enterprise usage of Jupyter: The business case and best practices for leveraging open source

Explorations in reproducible analysis with Nodebook- Kevin Zielnicki (Stitch Fix)

Flipped learning with Jupyter: Experiences, best practices, and supporting research

GenePattern Notebook: Jupyter beyond the programmer

Going native: C++ as a first-class citizen of the Jupyter ecosystem

How JupyterLab and widgets enable interactive analysis of the Earth's past, present, and future

I don't like notebooks.- Joel Grus (Allen Institute for Artificial Intelligence)

"If the data will not come to the astronomer. . ." - Adam Thornton (LSST)

Jupyter for every high schooler- Rob Newton (Trinity School)

Jupyter & Gravitational Waves - Will Farr (Stony Brook University)

Jupyter in the Enterprise - Luciano Resende (IBM Watson)

Jupyter Notebooks and the Intersection of Data Science - David Schaaf (Capital One)

Jupyter, sensitive data, and public policy- Julia Lane

Jupyter Trends in 2018 - Paco Nathan (derwen.ai)

Jupyter widgets- Maarten Breddels (Maarten Breddels), Sylvain Corlay (QuantStack)

JupyterLab and Plotly: A data visualization power couple- Lindsay Richman (McKinsey & Co.)

JupyterLab- Ian Rose (UC Berkeley), Chris Colbert (Project Jupyter)

Jupyter's configuration system

Keynote by Dan Romuald Mbanga (Amazon Web Services)

Learn by doing: Using data-driven stories and visualizations in the classroom

Making beautiful objects with Jupyter- M Pacer (Netflix)

nbinteract: Shareable interactive web pages from notebooks

Notebooks at Netflix: From analytics to engineering- Michelle Ufford (Netflix)

Open source software and the allocation of capital- Matt Greenwood (Two Sigma Investments)

Paul Ivanov (Bloomberg) interviewed at JupyterCon NY 2018

PayPal Notebooks: Data science and machine learning at scale, powered by Jupyter

Real-time collaboration with Jupyter notebooks using CoCalc- William Stein (SageMath, Inc)

Reproducible data dependencies for Jupyter - Jackson Brown, Aneesh Karve

Reproducible education: What teaching can learn from open science practices

Reproducible quantum chemistry in JupyterLab - Chris Harris (Kitware)

Reproducible science with the Renku platform- Sandra Savchenko-de Jong (Swiss Data Science Center)

Scaling collaborative data science with Globus and Jupyter - Ian Foster

Scaling notebooks for deep learning workloads - Luciano Resende (IBM Watson)

Scheduled notebooks: A means for manageable and traceable code execution- Matthew Seal (Netflix)

SoS: A polyglot notebook and workflow system...- Bo Peng (The University of Texas)

Supporting reproducibility in Jupyter through dataflow notebooks

Sustaining Wonder: Jupyter and the Knowledge Commons - Carol Willing (Cal Poly San Luis Obispo)

SWAN: CERN's Jupyter-based interactive data analysis service - Diogo Castro (CERN)

Terraforming Jupyter: Changing JupyterLab to suit your needs

The Emacs Ipython Notebook- John Miller (Honeywell UOP)

The Future of Data-driven Discovery in the Cloud - Ryan Abernathey (Columbia University)

The journey to Julia 1.0: The "Ju" in Jupyter

The Jupyter Notebook as a transparent way to document machine learning model development

The reincarnation of a notebook- Tony Fast (Ronin), Nick Bollweg (Georgia Tech Research Institute)

Using Jupyter notebooks in highly regulated environments

Using Jupyter to Empower Enterprise Analysts - Dave Stuart (Department of Defense)

Using the MapD kernel for the Jupyter Notebook- Randy Zwitch (MapD)

Visualizing high-dimensional biological data with Clustergrammer-Widget in the Jupyter Notebook

Visualizing machine learning models in the Jupyter Notebook- Chakri Cherukuri (Bloomberg LP)

What things are correlated with gender diversity: A dig through the ASF and Jupyter projects

When Jupyter Becomes Pervasive at a University? Fernando Perez (UC Berkeley)

2to3 converter를 활용한 django 프로젝트 python 버전업 삽질기 - 남형걸

3D 그래픽 그 안에서의 Python - 하호준

3명에서 3천명 이상이 된 파이썬 커뮤니티의 여정 - Manoj Pandey

40만명이 쓰는 Django channels 채팅서버 우리는 어떻게 만들었나? - 손은주

A Walk-through of Women Who Code Manila’s Python Study Group - Nicole I. Tibay

법률 네트워크 분석: 30년간의 변화 Changes in legal citation network over 30 years - 김재윤

비 개발자에게 파이썬 가르치기 - 문석환

Callosum: An RPC Tranport Library - 김준기

추천 시스템을 위한 어플리케이션 서버 개발 후기 @ kakao - 김광섭

땀내를 줄이는 Data와 Feature 다루기 - 박조은

Deep Dive into Coroutine - 김대희

드론 및 인공위성 영상을 이용한 태양광발전소 입지분석 - 최재현

딥러닝을 이용한 로그 기반의 게임 AI 개발 - 김선태

Dive Into 파이써니스쿨 - 2020년, 만약 모든 과목 선생님들이 파이썬을 배운다면? - 송석리

Django ORM 조금 더 깊게 살펴보기 - 한섬기

동물 홍채인식부터 서버까지 python으로 만들기 - 정진성

GDB와 strace로 Hang 걸린 Python Process 원격 디버깅 - 구영민

그렇게 커미터가 된다: Python을 통해 오픈소스 생태계 가르치기 - 신정규

'그리고 물고기는 고마웠어요' - 김무성

학습하는 조직과 파이썬: 뱅크샐러드 사례를 중심으로 - 황성현(hwangsunghyun)

하이퍼커넥트에서 자동 광고 성과 측정 시스템 구축하기 - 박승호, 정강식

How Python Saved My Life - Doni Rubiagatra

일반적인 케이스까지 포함한 파이썬을 이용한 의료 물리학 모델링 및 분석의 이해 - 최경돈

이무기: 파이썬으로 만드는 컴파일러 - 이한

인공지능 슈퍼마리오의 거의 모든것 - 정원석

인생은 짧아요 엑셀 대신 파이썬 - 이승준

작은 오픈 소스 3년 운영기 - 박아윤

진실은 언제나 하나! : Python으로 만나보는 Digital Forensic - 김동현

Luigi로 Data Pipeline system 구현하기 - 송은우

나도 할 수 있다 오픈 소스! — setup.py에서 PyPI까지 - 강효준

내가 배우는 이유, 내가 배우는 방법 - 송영숙

나누고 나누기: 파이썬으로 코드 리팩토링하기 - Niño R. Eclarin

네코유메: 파이썬으로 만든 블록체인 기반 롤플레잉 게임 - 김재석

Opening and Diamond Sponsor's Remarks at House Canary Room

파이썬에 switch문 넣기 : 새 구문을 만들면서 배우는 파이썬 내부 - 성우경

파이썬에서 함수형으로 프로그래밍하기 - 하원호

파이썬으로 암을 찾아보자: 데이터로 만드는 의학 이야기 - 백승욱

파이썬으로 학생 들여다보기 - 박윤곤

파이썬으로 네트워크 장비 테스트 자동화 하기 - 구동수

PyQt로 만드는 웹기반 데스크탑 어플리케이션 - 임덕규

Python and Rust (feat block-chain) # 파이선 그리고 러스트 (feat 블록체인) - Daniel Kim

Python으로 구현한 모바일 로봇 지능 - 하규태

Python으로 나만의 IoT 구축하기 - 박상우

Pythonic code가 과연 효율적일까? - 안주은

Quantify myself - self 사생활침해 - 이승훈

Raffle, Final Remarks and Conference Close

[라이트닝 토크] 아시아의 파이콘 - Noah Chen

[라이트닝 토크] 도도 파이터 소개 - 박준규

[라이트닝 토크] 컴퓨터 책 빨리 읽고 중고로 팔아버리기 - 김현지

[라이트닝 토크] Let's 문자통역 - 오시영(Siyoung Oh)

[라이트닝 토크] Meet Women Who Code Seoul - 이효은

[라이트닝 토크] multitasking with async - 곽재형(Jaehyung Kwak)

[라이트닝 토크] mypy 적용기 - 김민준

[라이트닝 토크] 파이썬으로 파이콘하기 - 박현우

[라이트닝 토크] 파이썬으로 토이프로젝트 만들기 - 권태관

[라이트닝 토크] 프로세서 구조로 보는 컴퓨터 역사 - 나승채

[라이트닝 토크] PyCon Diversity - 배권한(Kwonhan Bae)

[라이트닝 토크] PyCon US 2018 후기 - 조성수(Seongsoo Cho)

[라이트닝 토크] Python으로 LibreOffice의 한자(漢字) 공헌(貢獻 Contribution) - 성대현(Daehyun Sung)

[라이트닝 토크] Python으로 옮겨보자! 초급 C프로그램의 감성 - 윤성수(Seongsu Yoon)

[라이트닝 토크] Reinforcement Learning_A3C and RNN - 황현석

[라이트닝 토크] Selenium과 IE Driver로 만드는 커피 한 잔의 여유 - 조현진

[라이트닝 토크] 왜 나는 크립토에 현타가 왔는가? - 박진형

Ready,Get Set, Go! - 김영근

레거시 시스템에 Django 들이밀기 - 정지용(Jiyong Jung)

Ring: 프로그래밍 언어와 가까운 캐시 인터페이스 - 정윤원(Jeong Yunwon)

Running Python Code for IoT Projects on a custom-built Blockchain Network - Daniel Hong

생활탐사: 파이썬으로 일상에 도움 되는 뉴스 만들기 - 강종구

Sanic를 활용하여 Microservice 구축하기 - 이재면

소설 쓰는 딥 러닝 - 조용래

SW 의무교육 시대에서 살아남기 - 학생이 바라보는 교육자 - 박성우

Topic Modeling & Word Embedding 그리고 화장품 - 이홍주

우아하게 준비하는 테스트와 리팩토링 - 한성민

PyData 2018 - Day 2 - Hall 1

PyData 2018 - Day 2 - Hall 2

PyData 2018 - Hall 1

PyData 2018 - Hall 2

EuroPython 2018 - Closing

EuroPython 2018 - Lightning talks on Friday, July 27

EuroPython 2018 - Sprint Orientation

EuroPython 2018 - Lightning talks on Thursday, July 26

Keystone Sponsor Talk - Why Python is at the heart of Smarkets

EuroPython 2018 - Lightning talks on Wednesday, July 25

EuroPython 2018 - Opening Session

Sarah Diot Girard - Trust me, I'm a Data Scientist - ethics for builders of data based applications

Stephane Wirtel - What's new in Python 3 7

Конференция PyCon Russia 2018

Caipyra 2018: Como funciona um time remoto de desenvolvimento - Osvaldo Santana

Caipyra 2018: Computação Neuromórfica - Caroline Dantas

Caipyra 2018: Data Visualization in Tableau with TabPy - Nilton Kazuyuki Ueda

Caipyra 2018: Exceptions: e porque não são só para erros - Danilo Roberto Shiga

Caipyra 2018: Extraindo dados da internet usando Scrapy - Renne Rocha

Caipyra 2018: Hackeando a urna eletrônica brasileira com o Python - Paulo Matias

Caipyra 2018: Hey físicas e físicos! - Krissia Zawadzki

Caipyra 2018: Indicadores Inteligentes para Detecção de Epidemias de Dengue - Jadson Oliveira

Caipyra 2018: Internet Health Report - Geraldo Barros

Caipyra 2018: Introdução ao Machine Learning e NLP - João Rafael Martins

Caipyra 2018: Microservices em Python: desafios e soluções - Guilherme Vierno

Caipyra 2018: Processamento Paralelo para Pythonistas - Juliana Oliveira

Caipyra 2018: Python na Astronomia - Vitoria Ongaratto Baldan

Caipyra 2018: Tecnologia cívica: o que importa são as perguntas! - Eduardo Cuducos

Caipyra 2018: Teoria do Aprendizado Estatístico - Rodrigo Mello

Caipyra 2018: Visualizando query SQL a partir do ORM Django - Beatriz Uezu

Adopting Python Asyncio in Large Scale Project (Instagram) – Jimmy Lai – PyCon Taiwan 2018

初學者聯盟 The Beginners：超級英雄也是從初心者練起 – TsungWei Hu – PyCon Taiwan 2018

Communication strategies beyond the Basic Multilingual Plane – Katie McLaughlin – PyCon Taiwan 2018

Concurrency vs Parallelism

從螢幕閱讀程式—NVDA—探討資訊輔助科技與使用者介面可及性發展 – 曾奕勳 – PyCon Taiwan 2018

Crossing the Python 3 Rubicon – Claudiu Popa – PyCon Taiwan 2018

Deep Dive into Smart Contracts and Blockchains – Anand Sai, Aditthya R. – PyCon Taiwan 2018

Deep Learning for NLP: PyTorch vs Tensorflow – Elvis Saravia – PyCon Taiwan 2018

洞見驅動創新：利用 Keras，打造遊戲直播精彩剪輯 – 古宣佑 Hsuanyu – PyCon Taiwan 2018

Easy Way to Build a Real-Time Async Web with Django Channels – Yi-Chieh Chen – PyCon Taiwan 2018

Educational Code Reviews – 廖偉涵 Adrian Liaw – PyCon Taiwan 2018

from ai.backend import python – 曾君宇 – PyCon Taiwan 2018

該怎麼樣（認真的）部署你的 Python Web 應用程式? – Andy Dai – PyCon Taiwan 2018

Java-Jersey 到 Python-Flask 服務不中斷重構之旅 – Max Lai – PyCon Taiwan 2018

Lightning Talks and Closing – PyCon Taiwan 2018

MongoEngine Inside: The Detail of MongoDB & MongoEngine – 郭學聰 (Hsueh-Tsung Kuo) – PyCon Taiwan 2018

Opening – PyCon Taiwan 2018

PyCon Taiwan 2018 紀錄片

Python 工業 4.0—自造工廠監控系統 – Malo – PyCon Taiwan 2018

Python in Taiwan Photon Source: Motion Control, Data Logger and Chatbot – 林育正 – PyCon Taiwan 2018

Python 實作運彩下注策略 – 陳建安、廖子慶 – PyCon Taiwan 2018

人工智慧民主化在台灣 – 陳昇瑋 – PyCon Taiwan 2018

Smart Things + Home Assistant: Build Your Own Smart Home – Shuhsi Lin – PyCon Taiwan 2018

土炮一個 Line 股票機器人 – Victor Gau、沈弘哲、Malo – PyCon Taiwan 2018

Using Tensorflow on Stellar Classification – Poshih Chiang – PyCon Taiwan 2018

往 MVC GUI 設計邁進—Tkouter—支援 HTML-based Layout 的 Tkinter 擴充函式庫 – 袁克倫 – PyCon Taiwan 2018

維基教我做的金頭腦：知識圖譜製作初體驗 – 張泰瑋 – PyCon Taiwan 2018

小鴨城 (Duckietown)，一個基於 Raspberry Pi 和 ROS 的開源無人小車專案介紹 – sosorry – PyCon Taiwan 2018

心靈遊戲: 利用 Python 探索直覺物理 – Jiawei Chen – PyCon Taiwan 2018

以 Astroquery 套件擷取線上天文觀測資料 – 蘇羿豪 – PyCon Taiwan 2018

用 Python 來玩粒子物理實驗吧 – 黃坤賢 – PyCon Taiwan 2018

輿論分析量測電視劇觀看喜好的風向 Public Opinion Monitoring for TV Series – 魏聖倫 Kevin Wei – PyCon Taiwan 2018

這樣的開發環境沒問題嗎？ – Tzu-ping Chung – PyCon Taiwan 2018

自製高擴充性機器學習系統 – 徐愷、曾譯平 – PyCon Taiwan 2018

PyCon 9 - Lightning Talks

PyCon Italia 9 - An Italian dark vintage story

PyCon Italia 9 Goodbye and Closing

PyCon Italia 9 Welcome

Pycon Italia meets Concordia

[PySE 2018] API Star: novo framework REST do criador do DRF

[PySE 2018] Arquitetura de projetos Flask

[PySE 2018] Arquitetura do OpenEDX

[PySE 2018] Bot Command - Automatizando tarefas utilizando Python + Django + Telegram!

[PySe 2018] Cadê o paradigma? Teoria a serviço de Python na prática