Machine-Learning

이 과목에서는 기계학습 분야의 다양한 알고리즘을 실질적인 예제와 함께 공부한다.

수업에서 배워보는 알고리즘들에는 선형회귀방법, 로지스틱 회귀방법, 인공신경망 방법들이 있다.

모든 알고리즘들은 샘플 자료와 적절한 파이썬 코드로 구현하여 실습해 본다.

인공지능과 기계학습 개요

Lecture Notes : Intro.
Lecture Video

인공신경망의 역사

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Machine-Learning

인공지능과 기계학습 개요

인공신경망의 역사

Python Review

Linear Algebra (Review)

단변량 성형회귀(Linear Regression with one variable)

다변량 성형회귀(Linear Regression with multiple variable)

로지스틱 회귀 (Logistic Regression) - 분류

정규화 (Regularization)

신경망:표현 (Neural Networks : Representation)

신경망:학습 (Neural Networks : Learning)

SVM (Support Vector Machine)

기계학습 적용시 주의점

기계학습 시스템 설계

OCR example

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Name		Name	Last commit message	Last commit date
Latest commit History 62 Commits
.ipynb_checkpoints		.ipynb_checkpoints
data		data
images		images
.library.json		.library.json
0-1. Python for Machine Learning - Basic -Copy.ipynb		0-1. Python for Machine Learning - Basic -Copy.ipynb
0-1. Python for Machine Learning - Basic .ipynb		0-1. Python for Machine Learning - Basic .ipynb
0-1. Python for Machine Learning - Matplotlib -Copy.ipynb		0-1. Python for Machine Learning - Matplotlib -Copy.ipynb
0-1. Python for Machine Learning - Matplotlib .ipynb		0-1. Python for Machine Learning - Matplotlib .ipynb
0-1. Python for Machine Learning - Numpy-Copy.ipynb		0-1. Python for Machine Learning - Numpy-Copy.ipynb
0-1. Python for Machine Learning - Numpy.ipynb		0-1. Python for Machine Learning - Numpy.ipynb
0-2. Linear Algebra review-v1.ipynb		0-2. Linear Algebra review-v1.ipynb
0-2. Linear Algebra review-v2.ipynb		0-2. Linear Algebra review-v2.ipynb
0-2. Linear Algebra review.ipynb		0-2. Linear Algebra review.ipynb
0. Introduction.ipynb		0. Introduction.ipynb
1. Linear regression with one variable.ipynb		1. Linear regression with one variable.ipynb
2. Linear Regression with multiple variables.ipynb		2. Linear Regression with multiple variables.ipynb
3. Logistic Regression.ipynb		3. Logistic Regression.ipynb
4. Regularization.ipynb		4. Regularization.ipynb
5. Neural Neworks - Representation.ipynb		5. Neural Neworks - Representation.ipynb
6. Neural Networks - Learning.ipynb		6. Neural Networks - Learning.ipynb
6.1. Backpropagation.ipynb		6.1. Backpropagation.ipynb
6.2. Vectorization in python.ipynb		6.2. Vectorization in python.ipynb
7. Advice for applying machine learning.ipynb		7. Advice for applying machine learning.ipynb
8. Machine learning system design.ipynb		8. Machine learning system design.ipynb
9. Application example - Photo OCR.ipynb		9. Application example - Photo OCR.ipynb
ML Exercise #2-2 (problem) Regularization.ipynb		ML Exercise #2-2 (problem) Regularization.ipynb
ML Exercise #3 (problem) - Multi-Class Classification-v2.ipynb		ML Exercise #3 (problem) - Multi-Class Classification-v2.ipynb
ML Exercise #4 (problem) - Neural Networks-v2.ipynb		ML Exercise #4 (problem) - Neural Networks-v2.ipynb
ML Exercise 1-1 - Univariate Linear Regression (problem).ipynb		ML Exercise 1-1 - Univariate Linear Regression (problem).ipynb
ML Exercise 1-2 - Multivariate Linear Regression (problem).ipynb		ML Exercise 1-2 - Multivariate Linear Regression (problem).ipynb
Machine Learning Exercise #1 - Linear Regression.ipynb		Machine Learning Exercise #1 - Linear Regression.ipynb
Machine Learning Exercise #2-1 Logistic Regression.ipynb		Machine Learning Exercise #2-1 Logistic Regression.ipynb
Machine Learning Exercise #3 - Multi-Class Classification.ipynb		Machine Learning Exercise #3 - Multi-Class Classification.ipynb
Machine Learning Exercise #4 - Neural Networks.ipynb		Machine Learning Exercise #4 - Neural Networks.ipynb
Python Tutorial - Matplotlib.ipynb		Python Tutorial - Matplotlib.ipynb
README.md		README.md
Untitled.ipynb		Untitled.ipynb
desktop.ini		desktop.ini
ex3data2.h5		ex3data2.h5
ex4weights.h5		ex4weights.h5
ex4weights2.h5		ex4weights2.h5
exer1.py		exer1.py
exercise #2.ipynb		exercise #2.ipynb
fig2.png		fig2.png

infiniment/Machine-Learning

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Machine-Learning

인공지능과 기계학습 개요

인공신경망의 역사

Python Review

Linear Algebra (Review)

단변량 성형회귀(Linear Regression with one variable)

다변량 성형회귀(Linear Regression with multiple variable)

로지스틱 회귀 (Logistic Regression) - 분류

정규화 (Regularization)

신경망:표현 (Neural Networks : Representation)

신경망:학습 (Neural Networks : Learning)

SVM (Support Vector Machine)

기계학습 적용시 주의점

기계학습 시스템 설계

OCR example

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