Accelerate your NumPy Data Science Workloads and Deep Learning Applications

AI meets Fashion for product retrieval with multi-modally generated data

Build an AI-powered Pet Detector in Visual Studio Code

Building Named Entity Recognition Models Efficiently using NERDS

Carol Willing: Keynote

Datasets and machine learning models versioning using open source tools

Dynamic programming for machine learning: Hidden Markov Models

Fitting Many Dimensions into One: The Promise of Hierarchical Indices for Data Beyond Two Dimensions

IBM Code and Response: Open Sourcing Natural Disaster Preparedness and Relief

Machine Learning Model Evaluation Metrics

MAP all the things

Modeling Search Term Revenue: Using Embedding Layers to Manage High Cardinality Categorical Data

Open Source is Better Together: GPU Python Libraries Unite

Preparing messy data for supervised learning with vtreat

RAPIDS: Open Source GPU Data Science

Sameer Singh: Keynote | PyData LA 2019

Simplicity For Scale: Analyzing 15 Million DNA Samples With Python

Tackling Homelessness with Open Data

What You Got Is What You Got

A Guide to Modern Hyperparameter Tuning Algorithms

A "Supremely" Light introduction to Quantum Computing

A/B Testing in Python

Ahead in the Clouds: How to get started with serverless on Google, Amazon & Microsoft

Bokeh Maps: Making an interactive map for your next web application

Building a Data Driven Organization

Data and ETL with Notebooks in Papermill

Evaluation of Traditional and Novel Feature Selection Approaches

Gradient Boosting for data with both numerical and text features

Introducing Autoimpute: a Python Package for Grappling with Missing Data

Kyle Polich: Keynote | PyData LA 2019

Learning Topology: Topological Techniques for Unsupervised Learning

Lightning Talks | PyData LA 2019

Making data relevant to business. Its harder than you think!

Milana Lewis: Keynote | PyData LA 2019

To Production and Beyond: How to Manage the Machine Learning Lifecycle with MLflow

What's Data Science Reporting?

Write the Docs!

Analyzing genetic networks using neural networks

Computer Vision with PyTorch

Experimental Machine Learning with HoloViz and PyTorch in Jupyterlab

Git-ting along with others

Introduction to Data Analysis with Python datatable

Introduction to H2O AutoML with Python

Kedro + MLflow – Reproducible and versioned data pipelines at scale

Reinforcement Learning: Pac-Man

Turn Python Scripts into Beautiful ML Tools

Web Scraping w BeautifulSoup & Yelp's API