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jvar

JS inspired Variants and JSON parsing for C++

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

lstm_rnn_tutorials_with_demo

LSTM-RNN Tutorial with LSTM and RNN Tutorial with Demo with Demo Projects such as Stock/Bitcoin Time Series Prediction, Sentiment Analysis, Music Generation using Keras-Tensorflow

lstm_stock_price_prediction

Deep learning with long short-term memory networks for financial market predictions

machine-learning-for-beginner-by-python3

为机器学习的入门者提供多种基于实例的sklearn、TensorFlow以及自编函数(AnFany)的ML算法程序。

machinelearning

Machine learning resources，including algorithm, paper, dataset, example and so on.

ml-finance

Calculate technical indicators from historical stock data Create features and targets out of the historical stock data. Prepare features for linear models, xgboost models, and neural network models. Use linear models, decision trees, random forests, and neural networks to predict the future price of stocks in the US markets. Evaluate performance of the models in order to optimize them Get predictions with enough accuracy to make a stock trading strategy profitable.

mpl_finance

mpl_finance_ext

mpl_finance_ext provides functions to plot and evaluate finance data

neural-network-genetic-algorithm

Evolving a neural network with a genetic algorithm.

pandas-technical-indicators

Technical Indicators implemented in Python using Pandas

pmdarima

A package that brings R's beloved auto.arima to Python, making an even stronger case for why Python > R for data science.

pybacktester

An event-based backtester written in Python for algorithmic trading.

pyqtgraph

Fast data visualization and GUI tools for scientific / engineering applications

python-

scipy-lecture-notes

Tutorial material on the scientific Python ecosystem

star

A STock Analysis and Research tool for terminal(cli) users. 技术控和命令行爱好者的 A 股辅助分析工具。

stock-market-rnn-genetic-algorithm

A genetic algorithm that evolves generations of regression neural networks containing a combination of recurrent and dense layers.

stock-market-trader

A program to predict the stock market. ML Algorithms: Random Forest, Decision Trees ans also a CNN (TensorFlow) were implemented and their performance compared.

stock-price-prediction-model

Stock Price prediction using news data. The datasets used consists news and stock price data from 2008 to 2016. The polarity(Subjectivity, Objectivity, Positive, Negative, Neutral) data is gathered from the news data and further used to predict stock prices. Achieved an accuracy of 94% using XGBoost.

stock-price-prediction-with-indicators

The prediction is based on a recurrent neural network. The list of features includes MACD, Stochastic Oscillator, ATR, RSI etc.

stocknn

Stock Market Prediction Using Neural Network Models (Backpropagation, RNN LSTM, RBF) using keras with Tensorflow backend

stockprediction-svm

Semester Project for Stock Price Prediction

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.

stockrecommendationml

Stock Prediction with Mean Reversion model . (Machine Learning model is Droped)

techan.js

A visual, technical analysis and charting (Candlestick, OHLC, indicators) library built on D3.

tsfresh

Automatic extraction of relevant features from time series:

tutorials

机器学习相关教程

tutorials-1

CatBoost tutorials repository

webglsamples.github.io

WebGL Samples and Examples