Lecture

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Contents

Machine Learning

Natural Language Processing

Computer Vision and Pattern Recognition

Algorithm

Lecture slide

Chapter 1. Introduction [pdf]
Chapter 2. Divide and Conquer [pdf]
Chapter 3. DP [pdf]
Chapter 4. Greedy algorithms [pdf]
Chapter 5. Backtracking [pdf]
Chapter 6. NP theory [pdf]

C Programming

Lecture slide

Chapter 1. Introduction [pdf]
Chapter 2. Variables [pdf]
Chapter 3. Operators [pdf]
Chapter 4. Control statement [pdf]
Chapter 5. Function [pdf]
Chapter 6. Array [pdf]
Chapter 7. Pointer [pdf]
Chapter 8. String [pdf]
Chapter 9. Structure [pdf]

Data Structure

Lecture slide

Chapter 1. Introduction [pdf]
Chapter 2. Array and List [pdf]
Chapter 3. Stack and Queue [pdf]
Chapter 4. Priority queue and Heap [pdf]
Chapter 5. Sort [pdf]
Chapter 6. Indexing and Search Tree [pdf]
Chapter 7. Hash [pdf]
Chapter 8. Graph [pdf]

Deep Learning

Lecture slide

Chapter 1. Introduction [pdf]
Chapter 2. Neural network [pdf]
Chapter 3. EBPA [pdf]
Chapter 4. Gradient descent [pdf]
Chapter 5. Model tunning [pdf]
Chapter 6. CNN [pdf]
Chapter 7. RNN [pdf]
Chapter 8. Attention [pdf]
Chapter 9. Transformer [pdf]
Chapter 10. Generative models [pdf]
Chapter 11. Learning strategies & Neural architecture [pdf]

Practice

Chapter 2. Practice 1 [pdf]
Chapter 3. Practice 2 [pdf]
Chapter 4. Practice 3 [pdf]
Chapter 5. Practice 4 [pdf]
Chapter 6. Practice 5 [pdf]
Chapter 7. Practice 6 [pdf]
Chapter 8. Practice 7 [pdf]
Chapter 9. Practice 8 [pdf]
Chapter 10. Practice 9 [pdf]

Hadoop

Lecture slide

Chapter 1. 리눅스 개요와 환경 설정 [pdf]
Chapter 2. 리눅스 기본 명령어 [pdf]
Chapter 3. 파일 관리 [pdf]
Chapter 4. 쉘, 프로세스, 사용자, 유틸리티 명령어 [pdf]
Chapter 5. 디스크 관리 [pdf]
Chapter 6. 쉘 프로그래밍 [pdf]
Chapter 7. 병렬 프로그래밍 [pdf]

Machine Learning

Lecture slide

Chapter 1. Introduction [pdf]
Chapter 2. Regression [pdf]
Chapter 3. k-NN [pdf]
Chapter 4. SVM [pdf]
Chapter 5. Neural Network [pdf]
Chapter 6. DT and RF [pdf]
Chapter 7. Clustering [pdf]
Chapter 8. Feature Engineering [pdf]

Practice

Chapter 1. Practice 1 [pdf]
Chapter 2. Practice 2 [pdf]
Chapter 3. Practice 3 [pdf]
Chapter 4. Practice 4 [pdf]
Chapter 5. Practice 5 [pdf]
Chapter 6. Practice 6 [pdf]
Chapter 7. Practice 7 [pdf]
Chapter 8. Practice 8 [pdf]

Natural Language Processing

Lecture slide

Chapter 1. Introduction [pdf]
Chapter 2. Text mining techniques [pdf]
Chapter 3. Embedding [pdf]
Chapter 4. Transformer [pdf]
Chapter 5. LLMs [pdf]

Computer Vision and Pattern Recognition

Lecture slide

Chapter 0. Orientation [pdf]

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