Machine Learning: From Perceptron to CNNs and LSTMs

PPT 1: Discriminative and Generative Probability

Discriminative Probability: p(c|x)

Generative Probability: p(c) * p(x|c)

Examples:

  • Classification: Spam filtering, face recognition
  • Regression: Weather, stock trend prediction
  • Ranking: Web search, finding similar images
  • Collaborative Filtering: Recommendation
  • Clustering: Grouping similar things
  • Embeddings: Visualizing data

PPT 2: The Perceptron Algorithm

  1. Start with an all-zeros weight vector w1 = 0 and initialize t to 1. Automatically scale all examples x to
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