Price Prediction Case Study predicting the Bitcoin price and the Google stock price using Deep Learning, RNN with LSTM layers with TensorFlow and Keras in Python. (Includes: Data, Case Study Paper, Code)

Projects include the application of transfer learning to build a convolutional neural network (CNN) that identifies the artist of a painting, the building of predictive models for Bitcoin price data using Long Short-Term Memory recurrent neural networks (LSTMs) and a tutorial explaining how to build two types of neural network using as input the MNIST dataset, namely, a CNN using Keras and a fully-connected network using TensorFlow.

Python Bitcoin is widely used cryptocurrency for digital market. It is decentralised that means it is not own by government or any other company.Transactions are simple and easy as it doesn’t belong to any country.Records data are stored in Blockchain.Bitcoin price is variable and it is widely used so it is important to predict the price of it for making any investment.This project focuses on the accurate prediction of cryptocurrencies price using neural networks. We’re implementing a Long Short Term Memory (LSTM) model using keras; it’s a particular type of deep learning model that is well suited to time series data (or any data with temporal/spatial/structural order e.g. movies, sentences, etc.).We have used different activation function for analysing the efficiency of the system.Instead of historical data we are using live streaming data for better accuracy.

Predictive modeling for Bitcoin prices using LSTM and stacked neural nets

This repo contains backtesting scripts for various models(mainly LSTM) using different type of datasets to predict bitcoin price. 
Upto 98.7% accuracy, but let me tell you it’s not enough to generate profits on a regular basis ;)

This repo consist the code for Predicting Bitcoin Price using Deep Learning Method like RNN-LSTM

This is a guide on how you can implement time series in RNNs using LSTMs to determine the future prices of bitcoin

This project uses a Long Short-Term Memory (LSTM) model, a type of recurrent neural network, to predict the future price of Bitcoin.

This project leverages the Binance API to acquire real-time data for Bitcoin (BTC) and Ethereum (ETH). The data is then used to train a Long Short-Term Memory (LSTM) neural network model for predicting cryptocurrency prices.

Predict bitcoin price using gold and S&P 500 data implementing LSTM, Gradient Boosting Regression, and Random Forest

Building AI-powered Trading Bot to Predict Bitcoin Price Movements Using Deep Sequential Models and Ensemble Learning. A Comparative Study of LSTM, GRU, Transformer, and XGBoost.

Predicted the Price of the Cryptocurrency(Bitcoin) using the past time-series data, Twitter Sentiments(Polarity and Sensitivity), Currency's Fundamentals and Technical Indicators like RSI and SMA on LSTM. The Notebook contains the Exploratory data analysis(with important links) and the astounding result at the end of it

Using NLP and LSTM Neural Network to predict Bitcoin Prices

Predicting Bitcoin closing prices using deep learning models (GRU, LSTM, Bidirectional GRU) with feature selection and training on various time periods. Developed in Python using Jupyter Notebook.

Predicts Bitcoin prices using RNN LSTM

This project uses a Long Short-Term Memory (LSTM) neural network to predict the price of Bitcoin in US dollars. The LSTM model is implemented using the Keras library in Python.

Predicting Price of Bitcoin using LSTM.

A project aimed at predicting monthly Bitcoin prices for 2025 by analyzing historical Bitcoin price data using an LSTM model.

Use an LSTM RNN to predict bitcoin closing prices using historical price data and the Crypto Fear and Greed Index.

In this project we will explore about Bitcoin and also we will predict the price of bitcoin using Machine Learning algorithm..Here we will use LSTM model in Tensorflow to build our model and then we will predict the bitcoin price.

A short python script that use Recurrent Neural Network and LSTM to predict next period Bitcoin price from 30 previsous periods

focuses on predicting cryptocurrency price movements (e.g., Bitcoin, Ethereum) and modeling their market volatility using time series forecasting techniques like LSTM and ARIMA, and financial risk models like GARCH

Predict Bitcoin prices with ML & DL models! 📈 Uses Ridge, Lasso, Random Forest, MLP, RNN & LSTM with hyperparameter tuning. 📊 Visualizes predictions & ROC curves. 🚀 Fetch data via yfinance, evaluate with MSE/R2. Perfect for crypto enthusiasts! 💸

Bitcoin, the most famous decentralised digital currency, is the largest cryptocurrency globally in market capitalisation. It was introduced to the world for the first time in January 2009 and has had a volatile trading history ever since. The transactions occur via a Peer-to-Peer (P2P) network and are recorded in the blockchain, a public ledger. Here, an attempt has been made to predict, using regression (particularly LSTM), the closing price of Bitcoin at the end of each hour from 1st March 2016 to 24th November 2018 based on the available hourly data. It is multivariate because the closing price depends on the different prices, the volume traded, as well as trend, i.e. the popularity of the terms associated and time series as the values vary across time.

Using LSTM to predict Bitcoin price

​Predicting Bitcoin ₿ price 💵 based on previous data using LSTM

A very simple predictor for bitcoin prices using a LSTM neural network

Deep learning model for predicting Bitcoin price trends using TCN and LSTM.

This python script predicts the price of bitcoin using LSTM neural network

It is a small Time Series Analysis project using LSTM to predict Bitcoin price.