THIRD SEMESTERlabSem 3
MACHINE LEARNING LAB
CSS 3204
Syllabus
- 01Data Preprocessing for Financial Data
- 02Feature Selection for Financial Data
- 03Linear and Logistic Regression in Financial Trees and Random Forests for Risk Modeling and Credit Scoring
- 04Clustering Techniques for Market Segmentation
- 05Principal Component Analysis (PCA) for Portfolio Optimization
- 06Anomaly Detection in Financial Data Time Series Analysis for Stock Price Prediction
- 07LSTM and RNN for Financial Time Series Prediction
- 08Deep Learning for Fraud Detection
- 09Sentiment Analysis Using NLP for Market Prediction
- 10Portfolio Optimization using Deep Reinforcement Learning
References
- Marcos Lopez De Prado, ADVANCES IN FINANCIAL MACHINE LEARNING, John Wiley & Sons, Inc., Hoboken, New Jersey publication, 2018
- Yves Hilpisch, PYTHON FOR FINANCE MASTERING DATA-DRIVEN FINANCE, O'Reilly Media Publication, Second Edition, 2020
- Luigi Troiano, Arjun Bhandari, Elena Mejuto Villa, HANDS-ON DEEP LEARNING FOR FINANCE, Packt Publishing Ltd. Publication, 2020
- Pradeep Singh, FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING ALGORITHMS, Tools and Applications, Scrivener Publishing LLC, 2022
Credits Structure
0Lecture
0Tutorial
2Practical
1Total