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Machine Learning for All
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Classroom Contents
Gael Varoquaux at ODSC Boston 2015 - Scikit-Learn for Easy Machine Learning
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- 1 Intro
- 2 Vision
- 3 Classification
- 4 Regression Trees
- 5 Unsupervised Learning
- 6 Why Python
- 7 The Scientific Python Stack
- 8 Socket Image
- 9 Pythonic Code
- 10 Machine Learning for All
- 11 Conceptual Complexity
- 12 Estimator
- 13 Empire
- 14 Predict
- 15 Vectorizing
- 16 Transformer
- 17 Crossvalidation
- 18 Big Data
- 19 Online Algorithms
- 20 Metrics
- 21 Why ScikitLearn
- 22 Core contributors
- 23 Random forests
- 24 Build a communitydriven project
- 25 Limit technicality
- 26 Release packaging
- 27 Quality matters
- 28 Unit testing
- 29 Making it work
- 30 The vision
