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Machine Learning and Deep Learning Textbook - Cornell University

Another free book to learn Machine Learning. It also comes with a Youtube video series available here

Content

  • Machine Learning Setup
  • k-Nearest Neighbors / Curse of Dimensionality
  • Perceptron
  • Estimating Probabilities from data
  • Bayes Classifier and Naive Bayes
  • Logistic Regression / Maximum Likelihood Estimation / Maximum a Posteriori
  • Gradient Descent
  • Linear Regression
  • Support Vector Machine
  • Empirical Risk Minimization
  • Model Selection
  • Bias-Variance Tradeoff
  • Kernels
  • Kernels continued
  • Gaussian Processes
  • k-Dimensional Trees
  • Decision Trees
  • Bagging
  • Boosting
  • Neural Networks
  • Deep Learning / Stochastic Gradient Descent

You can access this material here. For other free tutorials (including from Berkeley, Harvard, Columbia, Google, Microsoft and so on), follow this link.

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