Description
Ever thought of "How to approach a Machine Learning Problem ?". This talk will guide you through pipeline for approaching a Machine Learning problem (Supervised) by taking up a real world problem which will make it easy for the audience to relate with. The task would be “Predicting like counts for a given YouTube video” and I would be taking you through the very first step of Data Collection to Model Evaluation, discussing various essential steps like Data analysis, Feature engineering, feature selection and many more along the way. Every step would be accompanied by some code snippets in Python using various scientific and ML libraries like Sklearn, Numpy etc.