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josehenriquedev

LSTM Bitcoin Prediction

2024

A deep learning pipeline using LSTM networks to forecast Bitcoin price trends from time-series data. Built in Python with Jupyter.

PythonLSTMMLPyTorch

Overview

Deep learning pipeline built in PyTorch/TensorFlow to analyze financial time-series data and forecast Bitcoin market trends.

The Challenge / Problem

Financial market data contains high volatility and noise, making linear models and traditional regressions inefficient for medium-term forecasting.

The Solution

Created a recurrent neural network (LSTM) using sliding time windows for feature engineering, normalization, and temporal validation.

Project Highlights

  • Feature engineering with technical indicators (RSI, MACD, Bollinger Bands)
  • LSTM model training with early stopping to prevent overfitting
  • Interactive notebooks with real vs predicted data visualizations