aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

pythonmachinelearning

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

pytorch-nlp-notebooks

Learn how to use PyTorch to solve some common NLP problems with deep learning.

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

pytorch-tutorial-on-google-colab

PyTorch Tutorial on google colaboratory.

ram

"Recurrent Models of Visual Attention" in TensorFlow

show-attend-and-tell

TensorFlow Implementation of "Show, Attend and Tell"

signet

SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification

somiao-pinyin

Somiao Pinyin: Train your own Chinese Input Method with Seq2seq Model 搜喵拼音输入法

springside4

A Spring Framework based, pragmatic style JavaEE application reference architecture.

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

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