Artificial intelligence (AI) is intelligence exhibited by intelligent agents(machines), rather than humans or other animals. AI research focus on the study of intelligent agents: any programmed device that senses its environment and takes actions that maximize its chance of success at some goal. Artificial intelligence concerns techniques that mimic human cognitive functions such as "learning" and "problem solving".
[Part I AI Intro & Agent Building]
- About the class
- AI Reasoning
- AI Search (DFS, BFS, Branch&Bound, A*)
- AI Search (Minimax, Alpha-Beta Pruning)
- Arduino Basics
- Aicar Building
[Part II Fundamentals of Machine Learning (Traditional Intelligence)]
- The Machine Learning Landscape
- End-to-End Machine Learning Project
- Classification
- Training Models
- Support Vector Machines
- Decision Trees
- Ensemble Learning and Random Forests
- Dimensionality Reduction
[Part III Neural Networks and Deep Learning (Deep Intelligence)]
- Up and Running with TensorFlow
- Introduction to Artificial Neural Networks
- Training Deep Neural Nets
- Convolutional Neural Networks
- Recurrent Neural Networks
- Autoencoders
- Reinforcement Learning
[Part I(Agent Building)]
[Part II Fundamentals of Machine Learning(Traditional Intelligence)]
- The Machine Learning Landscape
- End-to-End Machine Learning Project
- Classification
- Training Models
- Support Vector Machines
- Decision Trees
- Ensemble Learning and Random Forests
- Dimensionality Reduction
[Part III Neural Networks and Deep Learning(DeepLearning Intelligence)]