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What if you could take any TradingView Pine Script strategy or indicator, extract its market logic, and turn it into a machine-learning-powered trend prediction and scalping system?
In this video, I explain how to convert TradingView strategies and indicators into Python + LightGBM machine learning models that can learn market patterns, predict short-term trends, generate scalping signals, and ultimately be connected to an automated trading system.
π₯ What You’ll Learn
Convert TradingView Pine Script strategy/indicator logic into Python
Generate machine-learning features from technical indicators
Train a LightGBM model for market trend prediction
Predict Bullish, Bearish & Sideways market conditions
Build probability-based scalping signals
Combine technical indicators with machine learning
Generate automated entry and exit signals
Connect the ML model to an automated trading bot
Build a complete AI-powered trading workflow
π€ The Concept
TradingView Strategy β Python β Feature Engineering β LightGBM β Trend Prediction β Scalping Signal β Automated Trading
The goal is not simply to copy a TradingView strategy. Instead, we can use its underlying logic and market features as inputs for a machine-learning model that can discover patterns and generate probabilistic trading signals.
π Technologies Used
π Python
π§ LightGBM
π Pandas / NumPy
π TradingView Pine Script
π€ Machine Learning
β‘ Automated Trading
This approach can be applied to NIFTY, BANK NIFTY, SENSEX, futures, and options scalping systems.
β οΈ Disclaimer: This video is for educational and research purposes only. Machine learning does not guarantee profitable trades. Always backtest strategies and understand the risks before using any system with real money.
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