Quantra – Python for Machine Learning in Finance
This course is perfect for those looking to get started on using Python for Machine learning. Learn in a step-by-step fashion to create a Machine Learning algorithm for trading. Evaluate the performance of the machine learning algorithm and perform backtest, paper trading and live trading with Quantra’s integrated learning.
- Backtest, analyse the strategy returns and drawdowns, paper trade and live trade machine learning strategy
- Describe machine learning and its applications in finance
- List and implement common tasks in machine learning such as feature creation, training, forecasting, and evaluation in a step-by-step fashion
- Explain and implement accuracy, f1-score, recall and confusion matrix and R-squared
- Implement the train-test split for time series data
What You’ll Learn In Python for Machine Learning in Finance?
- Introduction
- Machine Learning Overview
- Introduction to Python
- Financial Market Data and Visualisation
- Machine Learning Tasks
- Target Variable and Features
- Machine Learning Algorithms
- Train-Test Split
- Training & Forecasting
- Metrics to Evaluate Classifier
- Introduction to Backtesting
- Live Trading on Blueshift
- Live Trading Template
- Metrics to Evaluate a Regressor
- Run Codes Locally on Your Machine
- Course Summary
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