Machine Learning and Language Modeling

Advancements in hardware devices and language models are propelling us into the age of artificial intelligence. Consequently, acquiring knowledge in both the theoretical and practical aspects of natural language processing (NLP) is crucial for delving deeper into industry applications. The objective of this course is to offer a comprehensive introduction to machine learning in relation to language models.

Prerequisites

• Topic 1 & 2: Basic vector calculus and Python programming (PyTorch)
  • Basic PyTorch Programming
  • Vector Calculus
• Topic 3 & 4: Knowledge of machine learning models (RNN, LSTM) and advanced PyTorch programming.
  • Advanced PyTorch Programming
  • Language Modeling

Topic	Slides	Code	Further Reading
Topic 1: Introduction to Machine Learning	Slides	Lab1
Topic 2: Word Embedding	Slides	Lab2
Topic 3: Self-Attention	Slides	Lab3
Topic 4: Transformer & Beyond	Slides	Lab4