Data-Science-Notes-master
所属分类：Windows编程
开发工具：Python
文件大小：31423KB
下载次数：0
上传日期：2020-03-22 16:12:10
上 传 者：
小文0822
说明： 在深度学习过程中，对数据进行处理的知识总结，包括numpy和pandas等等.
(In the process of deep learning, we summarize the knowledge of data processing, including numpy and pandas , etc)
文件列表:
0.math (0, 2019-11-22)
0.math\0.basic (0, 2019-11-22)
0.math\0.basic\1.机器学习的数学基础.pdf (1242015, 2019-11-22)
0.math\0.basic\markdown (0, 2019-11-22)
0.math\1.CS229 (0, 2019-11-22)
0.math\1.CS229\1.CS229-LinearAlgebra.pdf (1755150, 2019-11-22)
0.math\1.CS229\2.CS229-Prob.pdf (1221885, 2019-11-22)
0.math\1.CS229\markdown (0, 2019-11-22)
0.math\1.CS229\markdown\1.CS229-LinearAlgebra.md (58950, 2019-11-22)
0.math\1.CS229\markdown\2.CS229-Prob.md (27989, 2019-11-22)
0.math\1.CS229\markdown\images (0, 2019-11-22)
0.math\1.CS229\markdown\images\b958c16cfdce9e6bd2b810b10d71416e.png (15543, 2019-11-22)
0.math\1.CS229\markdown\images\c89fd93c5d6dccce89762d57fcd66dac.png (3694, 2019-11-22)
0.math\1.CS229\markdown\images\fig1.png (55167, 2019-11-22)
1.python-basic (0, 2019-11-22)
1.python-basic\a.txt (180, 2019-11-22)
1.python-basic\ly.txt (32, 2019-11-22)
1.python-basic\ly2.txt (32, 2019-11-22)
1.python-basic\test (76, 2019-11-22)
1.python-basic\两天入门python-第一天.ipynb (19459, 2019-11-22)
1.python-basic\两天入门python-第二天.ipynb (56432, 2019-11-22)
2.numpy (0, 2019-11-22)
2.numpy\1.numpy-beginner.ipynb (54280, 2019-11-22)
2.numpy\2.numpy.ipynb (48951, 2019-11-22)
2.numpy\images (0, 2019-11-22)
2.numpy\images\1.png (157459, 2019-11-22)
2.numpy\images\2.png (119185, 2019-11-22)
2.numpy\images\3.png (54791, 2019-11-22)
2.numpy\images\4.png (67493, 2019-11-22)
2.numpy\numpy-100 (0, 2019-11-22)
2.numpy\numpy-100\100_Numpy_exercises.ipynb (104614, 2019-11-22)
2.numpy\numpy-100\100_Numpy_exercises_no_solution.ipynb (34014, 2019-11-22)
2.numpy\numpy-100\100_Numpy_exercises_with_hint.ipynb (35323, 2019-11-22)
... ...
# Data-Science-Notes
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。
[0.math](0.math) (数学基础)
[1.python-basic](1.python-basic) (python基础)
[2.numpy](2.numpy)(numpy基础)
[3.pandas](3.pandas)(pandas基础)
[4.scipy](4.scipy)(scipy基础)
[5.data-visualization](5.data-visualization)(数据可视化基础,包含matplotlib和seaborn)
[6.scikit-learn](6.scikit-learn)(scikit-learn基础)
[7.machine-learning](7.machine-learning)(机器学习基础)
[8.deep-learning](8.deep-learning)(深度学习基础)
[9.feature-engineering](9.feature-engineering)(特征工程基础)
## 参考
- 《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](https://mooc.guokr.com/user/2133483357/)
- 《python科学计算》
## 关于作者
微信公众号:机器学习初学者 
知识星球:黄博的机器学习圈子
[我的知乎](https://www.zhihu.com/people/fengdu78/activities)
**注意:github下载太慢的话,关注我的公众号:“机器学习初学者”,回复“学习路线”即可下载本仓库的镜像文件,整个仓库压缩成一个iso。**
如果需要引用这个Repo:
格式: `fengdu78, Data-Science-Notes, (2019), GitHub repository, https://github.com/fengdu78/Data-Science-Notes`
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