GitHub

Finally updated my scikit-learn tutorial notebooks to work with Python 3 :)  #machinelearning

  • Comparing machine learning models in scikit-learn ( video , notebook , blog post )
  • Training a machine learning model with scikit-learn ( video , notebook , blog post )
  • Evaluating a classification model ( video , notebook , blog post )
  • Setting up Python for machine learning: scikit-learn and IPython Notebook ( video , notebook , blog post )
  • Efficiently searching for optimal tuning parameters ( video , notebook , blog post )

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@justmarkham: “Finally updated my scikit-learn tutorial notebooks to work with Python 3 🙂 #machinelearning”


scikit-learn-videos – Jupyter notebooks from the scikit-learn video series


GitHub

In-depth introduction to machine learning in 15 hours of expert videos

In-depth #MachineLearning in 15 hours of expert videos:  #BigData #DataScience by @Rbloggers

  • Lab: Model Selection Using Cross-Validation (5:32)
  • Lab: Forward Stepwise Selection and Model Selection Using Validation Set (10:32)
  • Chapter 7: Moving Beyond Linearity ( slides , playlist )
  • Lab: Random Forests and Boosting (15:35)
  • Multiple Linear Regression and Interpreting Regression Coefficients (15:38)

Read the full article, click here.


@KirkDBorne: “In-depth #MachineLearning in 15 hours of expert videos: #BigData #DataScience by @Rbloggers”


In January 2014, Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an


In-depth introduction to machine learning in 15 hours of expert videos