Software Engineering for Machine Learning
Preface
Introduction to Python
Version Control
Code Review
Testing
Web Services
Continuous Integration
Graphics
Reproducibility
Machine Learning
K-Means Clustering
Hierarchical Clustering
Principal Component Analysis
Practical Considerations of Clustering
Floating Point and Finite Precision
Supervised Machine Learning
Gradient Descent
Support Vector Machines
Neural Networks
Building the Book using Sphinx, GitHub Pages, and Travis
Sphinx Demonstration
Software Engineering for Machine Learning
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Neural Networks
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Neural Networks
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