Lecture 1 - NLP Foundation - Part I
Lecture 2 - NLP Foundation - Part II
Lecture 3 - Fundamentals of Machine Learning - Part I
Lecture 4 - Fundamentals of Machine Learning - Part II
Lecture 5 - Artificial Intelligence - An Introduction
Lecture 6 - Logistic Regression and Neural Networks
Lecture 7 - Large Scale SVM Algorithms and Applications
Lecture 8 - Ensemble Deep Learning For Alzheimer's Disease Dianosis
Lecture 9 - From Smart Sensing to Smart Living - The Era of IoT, AI:ML and Data Science
Lecture 10 - Machine Learning - Naive Bayes Classification
Lecture 11 - Cluster Analysis - Basic Concepts and Algorithms
Lecture 12 - Algorithms of Unsupervised Learning
Lecture 13 - Backbone functions of Deep Neural Networks Activation, Loss, Optimization functions
Lecture 14 - Convolutional Neural Networks
Lecture 15 - Reinforcement Learning - Experience, Adapt, Excel - Part I
Lecture 16 - Neoteric Frontiers in cloud, edge and Quantum Computing for Bigdata, IoT and AI Applications
Lecture 17 - Reinforcement Learning - Experience, Adapt, Excel - Part II
Lecture 18 - Economic Impact of New Category Recommendation Evidence from a Randomized Field Experiment
Lecture 19 - Neural Text Generation
Lecture 20 - RL Algorithms
Lecture 21 - An Overview of AI, NLP, ML Research Activities
Lecture 22 - LLMs and Ethics
Lecture 23 - Reinforcement Learning with Human Feedback
Lecture 24 - The LLM Journey
Lecture 25 - Representation Learning for Large Scale Pretrained Models
Lecture 26 - Computer Vision Application
