Notebooks & References:
- Universal Approximation Theorem - Michael Nielsen
- But what is a neural network? - 3Blue1Brown
- Machine Learning 101 - Jason Mayes, Google
What to do after the lecture?
- Run the Jupyter notebooks shared above (try other datasets)
- Ask and answer questions on this topic (scroll down)
- Start working on Assignment 4 - Data Science Competition
- Start working on Assignment 5 - Course Project
Asking/Answering Questions :
Reply on this thread to ask questions during and after the lecture. Before asking, scroll through the thread and check if your question (or a similar one) is already present. If yes, just like it. During the lecture, we’ll answer 8-10 questions with the most likes. The rest will be answered on the forum. If you see a question you know the answer to, please post your answer as a reply to that question. Let’s help each other learn!