This repo provides projects on deep-learning mainly using Tensorflow 2.0
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Updated
Aug 30, 2024 - Python
This repo provides projects on deep-learning mainly using Tensorflow 2.0
Stock Prediction & Forecasting Using Machine Learning (SVR And LSTM)
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Full-stack stock prediction web app. Frontend built with React, Tailwind CSS, and clerk for auth. Backend, powered by Python and Flask.
This project aims to predict stock prices using machine learning algorithms. By leveraging historical stock data and various features, we train predictive models to forecast future price movements. The goal is to provide users with actionable insights for making informed investment decisions
A Markov Model machine learning stock prediction algorithm
Welcome to my Lets Grow More internship project repository! Explore a collection of data science and business analytics projects showcasing my skills in predictive modeling, classification, and forecasting. Each project features a detailed Jupyter Notebook with code and visualizations. Join me on this data-driven journey!
This project predict Stock close price
Notes and Jupyter notebooks exploring deep learning and Tensorflow framework
Tensorflow and Sklearn(minmaxscler)
A program built to earn money automatically through stock trading, with little to no input from the user.
Mark Minervini's volatility contraction pattern detection, stage 2 template searching
dStock is a stock prediction program
네이버 주식 데이터를 크롤러를 통해 수집하고 LSTM을 이용하여 주식 가격을 예측했습니다.
Stock Price Prediction
The problem we are targeting here is to predict the future value of S&P500 given the past values. The key is to predict the value faster with increased accuracy in comparison to classical techniques. Here we used techniques in deep learning called Long-Short Term Memory(LSTM) that is used to learning the pattern occurring in temporal data. This …
ML project on stock market prediction with Japanese Candlestick Pattern Recognition for Ashoka University
순환신경망을 활용한 호가 데이터 기반의 주식시장 예측에 대한 연구 (A Study on the stock market prediction based on bid and ask information using recurrent neural network)
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