数据科学的笔记以及资料搜集,目前尚在更新,部分内容来源于github搜集。
1.python-basic (python基础)
2.numpy(numpy基础)
3.pandas(pandas基础)
4.scipy(scipy基础)
5.data-visualization(数据可视化基础,包含matplotlib和seaborn)
6.scikit-learn(scikit-learn基础)
7.machine-learning(机器学习基础)
8.deep-learning(深度学习基础)
9.feature-engineering(特征工程基础)
- 《统计学习方法》李航
- https://github.com/donnemartin/data-science-ipython-notebooks
- https://github.com/apachecn/feature-engineering-for-ml-zh
- https://github.com/datawhalechina/pumpkin-book
- https://github.com/Doraemonzzz/Learning-from-data
- https://github.com/wzyonggege/statistical-learning-method
- https://github.com/WenDesi/lihang_book_algorithm
- https://www.coursera.org/course/ml
- https://mooc.guokr.com/note/12/ 小小人_V
- 《python科学计算》
