Algorithmic Trading A-z With Python- Machine Le... -

from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import accuracy_score features = ['RSI', 'Returns', 'Volume'] X_train, y_train = train[features], train['Target']

import gym from stable_baselines3 import PPO class TradingEnv(gym.Env): # Define state (portfolio, prices), actions (buy/sell/hold), rewards (PnL) pass Algorithmic Trading A-Z with Python- Machine Le...

Disclaimer: This article is for educational purposes only. Trading financial instruments involves risk. Past performance does not guarantee future results. Consult a financial advisor before deploying real capital. from sklearn

From Data Feeds to Neural Networks: The Complete Pipeline y_train = train[features]

import backtrader as bt class MLStrategy(bt.Strategy): def (self): self.signal = self.datas[0].prediction # Your ML prediction column