머신러닝 공부 교재 참고

1. 파이썬 라이브러리를 활용한 데이터 분석

2. 혼자 공부하는 머신러닝 + 딥러닝

(강의) https://www.youtube.com/watch?v=J6wehCO_c58&list=PLVsNizTWUw7HpqmdphX9hgyWl15nobgQX

3. 파이썬 라이브러리를 활용한 머신러닝

4. 머신러닝 실무 프로젝트

5. 데이터 사이언스 입문 : 통계관점 (마케팅, 경영학, 통계학적 관점)

6. 비즈니스 데이터분석 입문 (마소캠퍼스) (마케팅, 경영학, 통계학적 관점)

- 참고 사이트

https://scikit-learn.org/stable/

scikit-learn: machine learning in Python — scikit-learn 1.0.1 documentation

Model selection Comparing, validating and choosing parameters and models. Applications: Improved accuracy via parameter tuning Algorithms: grid search, cross validation, metrics, and more...

scikit-learn.org

https://www.statsmodels.org/stable/index.html

Introduction — statsmodels

statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available

www.statsmodels.org

https://scipy.org/scipylib/

SciPy

Fundamental algorithms SciPy provides algorithms for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics and many other classes of problems. Broadly applicable The algorithms and data struc

scipy.org

https://numpy.org/

NumPy

Powerful N-dimensional arrays Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. Numerical computing tools NumPy offers comprehensive mathematical functions, random number g

numpy.org

https://pandas.pydata.org/

pandas - Python Data Analysis Library

pandas pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Install pandas now!

pandas.pydata.org

https://matplotlib.org/

Matplotlib: Python plotting — Matplotlib 3.4.3 documentation

matplotlib.org

https://github.com/ipython/ipyparallel

GitHub - ipython/ipyparallel: IPython Parallel: Interactive Parallel Computing in Python

IPython Parallel: Interactive Parallel Computing in Python - GitHub - ipython/ipyparallel: IPython Parallel: Interactive Parallel Computing in Python

github.com

- 참고 블로그

https://blog.naver.com/PostView.naver?blogId=baek2sm&logNo=222288167107&categoryNo=101&parentCategoryNo=0&viewDate=&currentPage=1&postListTopCurrentPage=1&from=search

사이킷런을 활용한 머신러닝(9) - 나이브 베이즈 분류(Naive bayes classification)

안녕하세요, 동네코더입니다. 이번에는 사이킷런을 활용한 머신러닝 9번째 포스팅으로, 집필중인 책의 원고...