Saturday, August 15, 2015

Saturday Morning Video: Machine Learning with Scikit Learn, Andreas Mueller & Kyle Kastner, SciPy 2015 Tutorial

Beware, the two parts of this tutorial by Andreas Mueller and Kyle Kastner lasts 6 hours in all:



 

All material is here: https://github.com/amueller/scipy_2015_sklearn_tutorial

Outline

Morning Session

  • What is machine learning? (Sample applications)
  • Kinds of machine learning: unsupervised vs supervised.
  • Data formats and preparation.
  • Supervised learning
    • Interface
    • Training and test data
    • Classification
    • Regression
  • Unsupervised Learning
    • Unsupervised transformers
    • Preprocessing and scaling
    • Dimensionality reduction
    • Clustering
  • Summary : Estimator interface
  • Application : Classification of digits
  • Application : Eigenfaces
  • Methods: Text feature abstraction, bag of words
  • Application : SMS spam detection
  • Summary : Model building and generalization

Afternoon Session

  • Cross-Validation
  • Model Complexity: Overfitting and underfitting
  • Complexity of various model types
  • Grid search for adjusting hyperparameters
  • Basic regression with cross-validation
  • Application : Titanic survival with Random Forest
  • Building Pipelines
    • Motivation and Basics
    • Preprocessing and Classification
    • Grid-searching Parameters of the feature extraction
  • Application : Image classification
  • Model complexity, learning curves and validation curves
  • In-Depth supervised models
    • Linear Models
    • Kernel SVMs
    • trees and Forests
  • Learning with Big Data
    • Out-Of-Core learning
    • The hashing trick for large text corpuses
 
 
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