Algorithmic Trading A-z With Python- Machine Le... 🔥
The "Algorithmic Trading A-Z with Python" curriculum commonly refers to a popular course created by Alexander Hagmann. This comprehensive resource covers everything from foundational financial concepts to deploying live trading bots in the cloud. Key Core Learning Areas
Strategy Engine: The logic that identifies entry and exit signals using technical indicators (e.g., RSI, Bollinger Bands) or AI models. Algorithmic Trading A-Z with Python- Machine Le...
Real Broker Integration: Connect Python scripts to live broker APIs such as OANDA, Interactive Brokers (IBKR), and FXCM. Syllabus & Core Topics Linear regression : for predicting continuous outcomes, such
- Linear regression: for predicting continuous outcomes, such as stock prices.
- Decision trees: for classifying data into different categories, such as buy or sell signals.
- Random forests: for ensemble learning and improving model performance.
scaler = MinMaxScaler() scaled = scaler.fit_transform(data[features]) scaler = MinMaxScaler() scaled = scaler
V. Cloud Deployment (AWS/GCP)
Your laptop cannot run 24/7. Deploy on a $10/month cloud server:
class MLStrategy(bt.Strategy): def init(self): self.signal = self.datas[0].prediction # Your ML prediction column
- "Python for Data Analysis" by Wes McKinney ( creator of Pandas)
- "Python Machine Learning" by Sebastian Raschka
- "Algorithmic Trading with Python" by Yves Hilpisch