Popular GitHub Repositories for Gasoline Prices

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

Using python and scikit-learn to make stock predictions

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

Train and Deploy an ML REST API to predict crypto prices, in 10 steps

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

Introducing neural networks to predict stock prices

Exploiting Bitcoin prices patterns with Deep Learning.

Acquiring data from Alpha Vantage and predicting stock prices with PyTorch's LSTM

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.

Using Transformer deep learning architecture to predict stock prices.

A comprehensive set of LLM benchmark scores and provider prices.

Pull stock prices from online API and perform predictions using Long Short Term Memory (LSTM) with TensorFlow.js framework

First Version.. Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT

FinTwit-Bot is a Discord bot designed to track and analyze financial markets by pulling data from platforms like Twitter, Reddit, and Binance. It features customizable tools for sentiment analysis, market trends, and portfolio tracking to help traders stay informed and make data-driven decisions.

Sentiment Analysis of news on stock prices

A Streamlit web app that predicts Singapore HDB resale flat prices using a pre-trained XGBoost model. Includes an interactive transaction map, light/dark theme toggle, and Docker support for easy deployment.

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

This project is about predicting stock prices with more accuracy using LSTM algorithm. For this project we have fetched real-time data from yfinance library.

This is a Python 3.0 project for analyzing stock prices and methods of stock trading. It uses native Python tools and Google TensorFlow machine learning.

A project using deep learning to forecast stock prices and covariance. Uses multiple threads to gather data and optimize portfolio using numerous APIs.