Machine Learning for Business Intelligence

Overview

A brief introduction will be given to the traditional financial world and the global Fintech market, with a dive into each category including lending, personal finance, payments, investments, equity financing, remittance, consumer banking, crowdfunding, and blockchain.

For each vertical in the banking industry, a brief explanation will be given for each sector of the Fintech industry, including applications, market insights with examples of real world case studies of multiple Fintech companies. Due to the strict global financial regulatory requirements, regulations set by the Malaysian Government institutions and other global leaders in FinTech will also be discussed under each segment.

Who Should Attend

Anyone who is keen to learn to learn more in-depth about Machine Learning and the real applications of Machine Learning for Business Intelligence today.

Prerequisites

Anyone working with Business Intelligence and Data Analysis.

Course Outline

• What is machine learning?
• Real-world data
• Modeling and prediction
• Model evaluation and optimization
• Basic feature engineering
• Example: NYC taxi data
• Advanced feature engineering
• Advanced Natural Language Processing (NLP) example: movie review sentiment
• Scaling machine-learning workflows
• Example: digital display advertising