Instructor Introduction
Lecture plan
강의목록
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Week 01: History of Artificial Intelligence and Machine Learning
- 1-1 Motivation and Turing Test - Can Machines Think?
- 1-2 Creation of Artificial Intelligence
- 1-3 Logical Artificial Intelligence - Expert System
- 1-4 Statistical Machine Learning
- 1-5 Neural Network and Deep Learning
- Quiz 1
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Week 02: Various Problems in Machine Learning
- 2-1 What are machine learning problems?
- 2-2 Learning with data and labels
- 2-3 Learning without labels
- Quiz 2
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Week 03: Finding Good Features to Solve Problems
- 3-1 What are good features and why are they important?
- 3-2 How to extract features automatically
- 3-3 What are composite features and why are they important?
- Quiz 3
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Week 04: Making Intelligence by Measuring the Similarity among Data Points
- 4-1 Distance Measures
- 4-2 Nearest Neighbor
- 4-3 Kernel Methods 1
- 4-4 Kernel Methods 2
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Week 05: Introduction to Neural Network
- 5-1 Artificial Neural Network
- 5-2 Convolutional Neural Network
- 5-3 Recurrent Neural Network
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Week 06: Participating in AI challenges
- 6-1 What are AI challenges?
- 6-2 Guide to Kaggle
- 6-3 Data Processing
- 6-4 Digit Recognizer
- Quiz 6
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Week 07: Participating in AI challenges (Advanced)
- 7-1 Methods of Ensemble
- 7-2 Avito Demand Prediction Challenge
- 7-3 Data Science Bowl 2018 & Toxic Comments