bobgxp Goto Github PK

aialpha

Use unsupervised and supervised learning to predict stocks

algo-etl

algotrade

algotrade

awesome-rl

Reinforcement learning resources curated

books-library

📚e-books in PDF and ePub formats across a wide range of technology stacks and topics

codefromvideo

Source code from the youtube video

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deep_trader

This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.

ds-algo

elegantrl

Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥

evolutionary-algorithm

Evolutionary Algorithm using Python, 莫烦Python 中文AI教学

findatapy

Python library to download market data via Bloomberg, Eikon, Quandl, Yahoo etc.

finrl

A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020. 🔥

fpp3-python-readalong

Python-centered read-along of Forecasting: Principles and Practice

machine-learning-for-trading

Code for Machine Learning for Algorithmic Trading, 2nd edition.

machinelearning

Machine learning and artificial intelligence

stock-prediction-models

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

stock-price-prediction-using-gan

In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.

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.