Applied Machine Learning - Stock Markets - Day 2

Day 1

• What is Machine Learning? what does a Machine Learn?
• Importance of data/features and predictability
• Time series data and predictability
• Nuances in Train data and test data split
• Stock market data, features, and predictability
• Descriptive Statistics and Feature Engineering
• First ML model

Day 2

• Predictive (supervised ML) modeling - Regression and classification - Hands-on
• Descriptive (unsupervised) modeling - clustering - Hands-on
• We will use Noteable / Weights and Biases / QuantSigns features
• Model to Strategy
• Simple forward-testing
• Further scopes