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

More courses from the same author: Quantra

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