Machine Learning Pointers

Supervised Learning

• Splines
• Bias, Variance, and Regularization in Linear Regression
• Regularization
• Intro to Naïve Bayes
• Naïve Bayes with Jupyter Notebook Example
• Naïve Bayes (YouTube)
• SVM Intro (YouTube, Stanford)
• SVM Intro (YouTube, Statquest)
• Random Forest Background (YouTube)
• Random Forest/Ensemble Background
• Advantages/Disadvantages of RF
• Hidden Markov Models (YouTube)
• Neural Network Playground

Unsupervised Learning

• Choosing k in k-means
• Intro to KDE (YouTube)
• Explanation of Density Estimation from sklearn docs
• 1D KDE Clustering Example
• Mixture Models Background
• Intro to EM (YouTube)
• EM Intro
• Using PCA, Visualizing PCA Results
• How to Read PCA Biplots, Scree Plots
• PCA and SVD Explained with Numpy

Visualization and Interpretation

• Formatting Seaborn Axis/Tick Labels
• Colormaps for Clustering
• Train/Test Split

Other

• Princeton ML Course
• Fourier Transform
• Human in the Loop
• Data Science Ethics Checklist

Good Notebooks

• Data Science in Python Cookbook
• Variety of Topics
• ML from Scratch