135 Open source projects that are alternatives of or similar to tesla-stocks-prediction

Introducing neural networks to predict stock prices

Automatic trading bot (WIP)

Web app to predict closing stock prices in real time using Facebook's Prophet time series algorithm with a multi-variate, single-step time series forecasting strategy.

Python3 project applying Gaussian process regression for forecasting stock trends

An attempt to predict next day's stock price movements using sentiments in tweets with cashtags. Six different ML algorithms were deployed (LogReg, KNN, SVM etc.). Main libraries used: Pandas & Numpy

Uses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.

Stock Market Analysis and Prediction is the project on technical analysis, visualization and prediction using data provided by Google Finance.

Predicting stocks with ML.

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Example of order book modeling.

Simple Stock Investment Recommendation System based on Machine-Learning algorithms for prediction and Twitter Sentiment Analysis.

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Use NLP to predict stock price movement associated with news

Online trading using Artificial Intelligence Machine leaning with basic python on Indian Stock Market, trading using live bots indicator screener and back tester using rest API and websocket 😊

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[NOT MAINTAINED] Predicting Bit coin price using Time series analysis and sentiment analysis of tweets on bitcoin

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A recurrent (LSTM) neural network in C

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A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!

Stock Market Predictor with LSTM network. Web scraping and analyzing tools (ohlc, mean)

😄 从此爸妈没烦恼！！！

A curated list of repositories for my book Machine Learning Solutions.

In these notebooks the entire research and implementation process carried out for the construction of various machine learning models based on neural networks that are capable of predicting levels of solar radiation is captured given a set of historical data taken by meteorological stations.

Courses, Articles and many more which can help beginners or professionals.

Plain Stock Close-Price Prediction via Graves LSTM RNNs

Hybrid Time Series using LSTM and Kalman Filtering

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

Smart Algorithms to predict buying and selling of stocks on the basis of Mutual Funds Analysis, Stock Trends Analysis and Prediction, Portfolio Risk Factor, Stock and Finance Market News Sentiment Analysis and Selling profit ratio. Project developed as a part of NSE-FutureTech-Hackathon 2018, Mumbai. Team : Semicolon

Stock Trading Bot using Deep Q-Learning

Unsupervised Learning to Market Behavior Forecasting Example

Stock price prediction using ensemble MLP in PyTorch.

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: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

A stock portfolio manager that provides neural net based short-term predictions for stocks and natural language processing based analysis on community sentiments.

[PAMI 2021] Gating Revisited: Deep Multi-layer RNNs That Can Be Trained

Trading Algorithm by XGBoost

A Machine Learning API with native redis caching and export + import using S3. Analyze entire datasets using an API for building, training, testing, analyzing, extracting, importing, and archiving. This repository can run from a docker container or from the repository.

Attempt to predict future stock prices based on Google Trends data.

Detect Sensitive REST API communication using Deep Neural Networks

Stock Price Predictor

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

Stock data analysis

Implementation of "Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading." In Findings of ACL2021

Using very simple code to compute indicator of stock\crytocurrency. For example, MA(C, 5) means average closed-price for last 5 days.

Use unsupervised and supervised learning to predict stocks

Paratope Prediction using Deep Learning

medium blog supplementaries | Backprop | Resnet & ResNext | RNN |

A siamese LSTM to detect sentence/question pairs.

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Inspired by the neural style algorithm in the computer vision field, we propose a high-level language model with the aim of adapting the linguistic style.

Stock for Deep Learning and Machine Learning

Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis

This repository contains the code for a conference paper "Predicting the football match winner using LSTM model of Recurrent Neural Networks" that we wrote

This is the realization of core DeepLog

Malware dataset for security researchers, data scientists. Public malware dataset generated by Cuckoo Sandbox based on Windows OS API calls analysis for cyber security researchers

Programs for stock prediction and evaluation

Strategies to Gekko trading bot with backtests results and some useful tools.