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