Machine Learning Basics

Pytorch based codes. Implementations of most popular algorithms at present.

Basic Neural Networks:

./MultinomialLogisticRegression_NeuralNetwork: Neural Network with L1 and L2 penalty;

./MultinomialLogisticRegression_NeuralNetwork: Logistic Regression;

./Resnet_CNN: Resnet, CNN forward implementation from scratch;

./Audio_processing_RNN_GRU_LSTM: RNN, GRU, LSTM for autio signal processing;

./AE_VAE_CAE_CVAE: Autoencoder (AE), Convolutional Autoencoder (CAE);

./AE_VAE_CAE_CVAE: Variational Autoencoder (VAE), Convolutional Variational Autoencoder (CVAE);

./CAE_CGAN: Deep Convolutional GAN (DCGAN);

./GaussianProcess: Gaussian Process;

./Bayesian_Optimization: Bayesian Optimization for Neural Network hyperparameters searching;

./Sampling: Metropolis-Hastings Sampling, Gibbs Sampling;

./NLP_Offensive_Language_Detection

./Forests_Boosting: Random Forests, Decision Tree, Adaboosting;