Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
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Updated
Jul 28, 2022 - Python
Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis
Use unsupervised and supervised learning to predict stocks
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
Use NLP to predict stock price movement associated with news
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Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIM…
Uses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.
Portfolio optimization with deep learning.
Simple to use interfaces for basic technical analysis of stocks.
多因子指数增强策略/多因子全流程实现
This tool should help discover different patterns based on similarity measures in historical (financial) data
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Examples of python neural net and ML stock prediction methods with sample stock data.
Stock price prediction using LSTM and 1D Convoltional Layer implemented in keras with TF backend on daily closing price of S&P 500 data from Jan 2000 to Aug 2016
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Find your trading, investing edge using the most advanced web app for technical and fundamental research combined with real time sentiment analysis.
Python3 project applying Gaussian process regression for forecasting stock trends
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