Finance Practitioners and Machine Learners eager to learn ML techniques in Finance and Implementation of ML projects in Finance.

09:00 - 10:30 | PART 1
Quantitative Finance

• Review Quantitative Finance
• Alternative data

Machine Learning Modeling

• Mathematics of Machine Learning
• Machine Learning Modeling Framework

10:45 - 12:00 | PART 2
Supervised Learning: Classification

• Logistic Regression and Softmax Regression
• SVM's and CART's

Ensembles

• Boosting and Bagging: Random Forests
• AdaBoost + XG Boost

12:00 - 13:00 | LUNCH BREAK

13:00 - 14:30 | PART 3
Supervised Learning: Regression

• Modern Linear Regression
• Non-Linear Regression
• Neural Networks
• Deep Neural Networks

14:30 - 16:00 | PART 4
Supervised Learning: Deep Learning

• Mathematics of Deep Learning
• Deep Learning Architectures

Reinforcement Learning Natural language Processing

• Sentiment analysis - NLTK

16:00 - 17:30 | PRACTICAL
Python and Exercises

Mathematics + Python + Applications

• laptop with Python installed