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benny-abhishek / repository
A python based project to predict the future prices of the top 10 trending cryptocurrencies using ML Algorithms like SVR, Decision Tree and LSTM with an interactive frontend using streamlit. Analysis using PowerBi and has DBMS connectivity.
A python based project to predict the future prices of the top 10 trending cryptocurrencies using ML Algorithms like SVR, Decision Tree and LSTM with an interactive frontend using streamlit.
Streamlit sklearn pandas tensorflow yfinance
Support Vector Regeression (SVR) RNN-LSTM (Recurrent Neural Networks & Long Short Term Memory) Decision Tree Linear Regression
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Harshit28j /
A simple program that can show you predicted visualization of cryptocurrency market based on previous data sets so , Supervised Learning
aylazai /
This project is a Python script that uses machine learning logistic regression to predict stock and crypto prices (or rather returns). The model is based on a classification model that takes the prior N days' asset directions and predicts the return. The direction of the asset determines whether it should be bought or sold.
Cryptocurrency [ETH/USDT] prediction with RNN Neural Network Artificial Intelligence - Emirhan BULUT I developed Cryptocurrency [ETH/USDT] prediction with RNN Neural Network software with Artificial Intelligence. I predicted the fall on February 24, 2022 with 98.21% accuracy in the ETH/USDT pair. '0.03979729297154955' MAE Score, '0.0023235646943942415' MSE Score, 98.35% Accuracy Question software has been completed. The ETH/USDT pair forecast for February 24, 2022 was correctly forecasted based on data from Binance. Software codes and information are shared with you as open source code free of charge on GitHub and My Personal Web Address. Happy learning! Emirhan BULUT Senior Artificial Intelligence Engineer and Inventor The coding language used: Python 3.9.8 Libraries Used: Tensorflow - Keras NumPy Matplotlib Pandas Scikit-learn (SKLEARN)
Code-With-Shanmukh /
Developed a real-time cryptocurrency price prediction system using Python. The project fetches live crypto market data using CCXT, preprocesses it, and applies an LSTM model to predict future prices. A Tkinter-based GUI visualizes actual vs. predicted prices and provides alerts for significant price drops.
Siddharth038 /
Developed a Python-based system for predicting cryptocurrency prices. Utilized normalization techniques for enhanced accuracy
abhiramkrishnan036 /
AI-based Crypto Prediction Agent built using Python and agent architecture. The system fetches crypto data, predicts price movement, applies Kelly risk management, and evaluates prediction accuracy with logging and result tracking.