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Welcome
Prerequisites
Lectures
Lecture 1: Introduction
Lecture 2: Linear models
Lecture 3: Kernelization
Lecture 4: Model Selection
Lecture 5. Ensemble Learning
Lecture 6. Data preprocessing
Lecture 7. Bayesian Learning
Lecture 8. Neural Networks
Lecture 9: Convolutional Neural Networks
Lecture 10. Neural Networks for text
Labs
Lab 1a: Linear regression
Lab 1b: Linear classification
Lab 2a: Kernelization
Lab 2b: Model selection
Lab 3: Ensembles
Lab 4: Data preprocessing
Lab 5: Bayesian models
Lab 6: Neural networks
Lab 7a: Convolutional neural nets
Lab 7b: Neural Networks for text
Lab 8: AutoML
Tutorials
Python for data analysis
Python for scientific computing
Machine Learning in Python
Recap: Decision Trees
Recap: k-Nearest Neighbor
Lab 1: Machine Learning with Python
Lab 2: Model Selection in scikit-learn
Lab 4: Data engineering pipelines
Lab 6: Deep Learning with TensorFlow
Lab 7: Deep Learning for text
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