1 Table of Contents: “... -- Probability -- Hypothesis and inference -- Gradient descent -- Getting data -- Working with data -- Machine...”

2 “... into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic...”

3 Table of Contents: “... -- Dimensionality Reduction -- For Further Exploration -- Modeling -- What Is Machine Learning? -- Overfitting...”