quantumiracle / Machine_Learning_Basic_Algorithms-Pytorch

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

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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;

Generative Model:

./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);

Gaussian Process:

./GaussianProcess: Gaussian Process;

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

Sampling:

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

NLP for Offensive Language Detection:

./NLP_Offensive_Language_Detection

Others:

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

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

License:MIT License


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