SECTION 1 - Introduction
SECTION 2 - Setting up your Python Integrated Development Environment (IDE) for Course Labs
SECTION 3 - Regression
SECTION 4 - Linear Regression
SECTION 5 - Decision Tree - Classification and Regression Trees
SECTION 6 - Random Forests
SECTION 7 - Classification
SECTION 8 - Logistic Regression
SECTION 9 - K Nearest Neighbors
SECTION 10 - Support Vector Machines (SVM)
SECTION 11 - Naive Bayes
SECTION 12 - Clustering
SECTION 13 - K - Means Clustering
SECTION 14 - Hierarchical Clustering
SECTION 15 - Associated Rule Learning
SECTION 16 - Eclat and Apior
SECTION 17 - Dimensionality Reduction
SECTION 18 - Principal Component Analysis
SECTION 19 - Linear Discriminant Analysis LDA
SECTION 20 - Neural Networks
SECTION 21 - Artificial Neural Networks
SECTION 22 - Convolutional Neural Networks
SECTION 23 - Recurrent Neural Networks
SECTION 24 - Conclusion and Bonus Section
