BissTrade

🧠 LSTM AI Model Predicts BTC Move on the 4H Chart ⚡I've built and trained an LSTM (Long Short-Term Memory) deep learning model specifically to analyze 4-hour BTC chart data — and it's showing some strong signals.📚 What the model does:The LSTM takes recent 4H candlestick data and learns from historical trends, volatility patterns, and short-term momentum. With ~96% accuracy on training data, it's shown solid potential in picking up turning points and projecting short-term moves.🚀 Current Prediction:The model suggests Bitcoin is on track to push toward $70K, continuing its current uptrend within the next 30 days if momentum holds.This isn’t just a moving average crossover — this is deep learning trained to recognize complex crypto behavior.⚠️ Disclaimer:As always, no model is perfect. This is a forecast, not financial advice. Use it as a perspective, not a guarantee.Let me know if you're seeing similar signs, or if you're using ML in your trading too! 🔍#BTCUSD #Bitcoin #CryptoForecast #4HChart #LSTMModel #AITrading #BTCto70K #CryptoAnalysis

📈 Bitcoin to $70K? My LSTM Model Thinks So 🚀I've been working on an LSTM (Long Short-Term Memory) neural network designed to forecast Bitcoin prices, and the results are exciting. My model analyzes historical BTC data and learns temporal patterns to predict future movements. After extensive training and optimization, it reached an accuracy of around 96% on the training set.🔍 How it works:LSTM networks are especially powerful for time-series forecasting because they can capture long-term dependencies and trends in data. I trained my model using historical daily BTC prices, letting it learn the complex patterns and volatility that define crypto markets. The model takes sequences of past prices and uses that context to project the price movements of the next 30 days.📊 The Forecast:Based on the model's output, my current prediction is that Bitcoin will reach $70,000 within the next 30 days. This projection isn’t just a guess – it’s backed by a deep-learning model built to handle the chaotic nature of crypto.⚠️ Note:While the training accuracy is high, real-world conditions can differ, and models should always be taken as tools—not certainties. I’m sharing this analysis to contribute to the community and spark discussion.Would love to hear your thoughts or see if others are seeing similar trends! 👇#Bitcoin #BTC #CryptoAnalysis #MachineLearning #LSTM #BitcoinForecast #CryptoTrading