work experience

This project contains comprehensive teaching materials developed for tutoring a graduate student in Machine Learning. The course covers:

  1. Python data types introduction
  2. Basic data structures and transformation
  3. Exploratory Data Analysis (EDA)
  4. Data preprocessing techniques
  5. Data modeling
  6. Introduction to PyTorch
  7. Practical Projects:
    • Machine Learning: Titanic survival prediction
    • Deep Learning: Field-weighted Factorization Machines (FwFMs) implementation

This curriculum provides a structured approach to learning ML concepts, from foundational Python skills to advanced deep learning applications, with hands-on projects for practical experience.