머신러닝 커리큘럼

캐글 titanic dataset 공부계획입니다.

1. 파이썬기초

https://www.kaggle.com/mjbahmani/the-data-scientist-s-toolbox-tutorial-1

2. 파이썬 패키지 기초

https://www.kaggle.com/mjbahmani/the-data-scientist-s-toolbox-tutorial-2

3. 간단한 수학연산

https://www.kaggle.com/mjbahmani/linear-algebra-for-data-scientists

4. 분석툴

https://www.kaggle.com/mjbahmani/20-ml-algorithms-15-plot-for-beginners

5. 빅데이터처리방법

https://www.kaggle.com/mjbahmani/a-data-science-framework-for-quora

6. 데이터 시각화

https://www.kaggle.com/mjbahmani/top-5-data-visualization-libraries-tutorial

7. 데이터 클리닝

https://www.kaggle.com/mjbahmani/machine-learning-workflow-for-house-prices

8. 문제해결법

https://www.kaggle.com/mjbahmani/the-data-scientist-s-toolbox-tutorial-2

9. 머신러닝 실습

https://www.kaggle.com/mjbahmani/a-comprehensive-ml-workflow-with-python

10. 딥러닝실습

https://www.kaggle.com/mjbahmani/top-5-deep-learning-frameworks-tutorial