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