Weekly Resources# Week 1# What is Data Mining & Data Mining Tasks? How to use Google Colab Introduction to Python Week 2# Introduction to Numpy Introduction to Pandas Math Essentials Probability NumPy Cheat Sheet Pandas Cheat Sheet scikit-learn Cheat Sheet matplotlib Cheat Sheet Week 4# Colab to GitHub KL-Divergence California Housing Prices Dataset Week 5# Spearman’s Rank-Order Correlation Student t-test for Pearson Correlation Week 6# Midterm Exam Topics Project Overview Proposal Bag of Words Word Embeddings TF-IDF Word2vec Tutorial Word2vec Explained Distributed Representations of Words and Phrases and their Compositionality Neural Word Embedding as Implicit Matrix Factorization Word2vec Parameter Learning Explained Stemming vs. lemmatization Week 8# Bayesian network Week 12# What is Back Propagation? Week 13# Understanding Deep Learning (Still) Requires Rethinking Generalization video paper Understanding Long Short-Term Memory Networks (LSTMs) - Chris Olah The Illustrated Transformer - Jay Alammar Attention is all you need Week 14# Model selection and training/validation/test sets Nuts and Bolts of Applying Deep Learning Transformers Explained Visually: Learn How LLM Transformer Models Work The tool The paper
