In this folder contains jupyter notebooks for the labs, midterm and final exam.
- AML_lab1 : Creating a Data Science Repository, about PyTorch and Torchvision installation, Simple Neural network with PyTorch, Tensorboard
- AML_lab2 : Neural Network Architectures: CNN and Training Nets, Training Simple CNN Model & Transfer Learning for CNN
- AML_lab3 : Movie Sentiment Analysis with RNN
- AML_lab4 : Simple and staked LSTM & Transformer based models
- AML_lab5 : HMM for POS tagging, Viterbi Algorithm example & CG rich region identification
- AML_lab6 : Genetic Algorithms & Evolution Theory
- AML_lab8 : Content based recommendation Systems, Matrix Factorisation & Deep Learning based recommendation systems
- AML_lab9 : Recap Auto-encoder PyTorch implementation & Vanila GAN Training
- AML_lab10 : Stationarity in time series & ARIMA
- AML_lab11 : Interpretable AI -> Interpret Microsoft, LIME & SHAP
- AML_lab12 : Reinforcement Learning implementation -> Deep Q-learning with PyTorch