Perceptron Summer 2017 (Machine Learning Course)
Coding Blocks, Pitampura.
Contents
- Class_01: Introduction to Python and Machine Learning
- Class_02: K-Nearest Neighbours
- Class_03: Face Recognition with KNN
- Class_04: K-Means clustering and Most Dominant Color extraction
- Class_05: Decision Trees and Random Forests
- Class_06: Principal Component Analysis
- Class_07: Linear Regression
- Class_08: NeuralNets w/ Keras
- Class_09: Neural Nets (numpy), MNIST classification, AutoEncoder (stacked, simple)
- Class_11: ConvNets and Conv Auto Encoders
- Class_13: Transfer Learning, Differential Evolution, Genetic Algorithm
- Class_14: Markov chains, intro to RNN
- Class_15: RNN for Addition, LSTM for image generation
- Class_16: Deep Dream and Neural Art
- Class_17: Naive Bayes and SVM
- Class_18: Word2Vec and Scraping
- Class_19: Attention mechanism
- Class_20: Simple RL and Q-leanring
- Class_21: Deep Q-learning and Sentiment Analysis
- Class_22: Generative Adversarial Networks