unosonu,github

stanford-cs-221-artificial-intelligence

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

stargan

Official PyTorch Implementation of StarGAN - CVPR 2018

starspace

Learning embeddings for classification, retrieval and ranking.

stock-prediction-models

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

Listens for Stock news on Twitter, performs sentiment analysis by mining information from an online news source, performs supervised predictive modeling and suggests buy or sell decisions of the stock. Computes portfolio returns over time.

stock_price_predication

I have implemented Recurrent Neural Network (RNN model) to predict the future stock prices and compare it with linear regression.

stockanalysis

stockmarketgan

Stock Market Prediction Using Unsupervised Features

stockpredictionai

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.