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Welcome to your Jupyter Book
Core Modules
Module 1 Python Primers
1.1 Python Basics
1.2 Intermediate Python
Module 10: Supervised Machine Learning
10.0: Introduction
10.1: Data Preparation and Feature Engineering
10.2: Naive Bayes and Model Construction
10.3: Evaluating and Interpreting Models
10.4: Pipelines, Persistence, and Reproducible Inference
10.5 Random Forest and Model Complexity
Appendices
Appendix 1: Getting Set Up
Appendix 1.1: Linux & WSL
Appendix 10: Supervised Machine Learning
A10.1 BioAssay Screening: Enough Actives
A10.2 Bayes’ Theorem: From Inference to Models
Repository
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Module 10: Supervised Machine Learning
Module 10: Supervised Machine Learning
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