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Perceptron Summer 2017 (Machine Learning Course)

Coding Blocks, Pitampura.

Contents

  1. Class_01: Introduction to Python and Machine Learning
  2. Class_02: K-Nearest Neighbours
  3. Class_03: Face Recognition with KNN
  4. Class_04: K-Means clustering and Most Dominant Color extraction
  5. Class_05: Decision Trees and Random Forests
  6. Class_06: Principal Component Analysis
  7. Class_07: Linear Regression
  8. Class_08: NeuralNets w/ Keras
  9. Class_09: Neural Nets (numpy), MNIST classification, AutoEncoder (stacked, simple)
  10. Class_11: ConvNets and Conv Auto Encoders
  11. Class_13: Transfer Learning, Differential Evolution, Genetic Algorithm
  12. Class_14: Markov chains, intro to RNN
  13. Class_15: RNN for Addition, LSTM for image generation
  14. Class_16: Deep Dream and Neural Art
  15. Class_17: Naive Bayes and SVM
  16. Class_18: Word2Vec and Scraping
  17. Class_19: Attention mechanism
  18. Class_20: Simple RL and Q-leanring
  19. Class_21: Deep Q-learning and Sentiment Analysis
  20. Class_22: Generative Adversarial Networks

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