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.
The problem to be discussed : https://github.com/ayush1997/YouTube-Like-predictor
Ayush Singh Ayush Singh
Ayush is a Computer Science Undergrad from India currenly working as a Research Intern @Swarath lab,IIITD on Self Driving Cars.He is passionate about learning new stuff and mentoring people.He has an ardent interest in Machine Learning,Data Science and Deep Learning and has been working on some interesting real world problems in these domains and is also a part of Stanford's Scholar program. He is a FOSS enthusiast and also mentor at his college's FOSS and Development Society. He frequently gives open talks in his college and other community meetups on DataScience,ML and many other stuff.He is a Hackathon lover too.