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[Udemy] Data Analysis In-Depth (In Python) (10.2021)
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[Udemy] Data Analysis In-Depth (In Python) (10.2021)
磁力链接/BT种子简介
种子哈希:
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收录时间:
2022-03-14
最近下载:
2024-10-16
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文件列表
22. Day 20 A - EDA Cont.mp4
1.4 GB
8. Day 8 - Statistics for Data Analysis - Statistical Hypothesis.mp4
1.3 GB
18. Day 17 - Pandas.mp4
1.3 GB
19. Day 18 - Seaborn.mp4
1.2 GB
14. Day 13 - Numpy.mp4
1.2 GB
12. Day 11 - Python for Data Analysis.mp4
1.2 GB
6. Day 6 - Statistics for Data Analysis - Probability.mp4
1.2 GB
5. Day 5 - Statistics for Data Analysis - Probability.mp4
1.2 GB
17. Day 16 - Pandas.mp4
1.2 GB
11. Day 10 - Python for Data Analysis.mp4
1.1 GB
7. Day 7 - Statistics for Data Analysis - Probability.mp4
1.1 GB
4. Day 4 - Statistics for Data Analysis - Probability.mp4
1.1 GB
1. Day 1 - Introduction to Data Science.mp4
931.3 MB
13. Day 12 - Python for Data Analysis.mp4
896.7 MB
15. Day 14 - Pandas.mp4
858.0 MB
2. Day 2 - Introduction to Data Analytics.mp4
852.2 MB
3. Day 3 - Statistics for Data Analysis - Scalar, Vectors and Matrix.mp4
849.2 MB
16. Day 15 - Pandas.mp4
829.1 MB
10. Day 9B - Python for Data Analysis.mp4
822.6 MB
20. Day 19 A - Seaborn.mp4
615.3 MB
21. Day 19 B - EDA.mp4
397.5 MB
9. Day 9A - Statistics for Data Analysis - Statistical Hypothesis.mp4
262.9 MB
23. Day 20 B - What Next.mp4
242.4 MB
3.1 Machine _Learning Day 3.pdf
28.9 MB
8.1 Machine _Learning Day 8.pdf
26.2 MB
4.1 Machine _Learning Day 4.pdf
18.2 MB
6.1 Machine _Learning Day 6.pdf
15.1 MB
7.1 Machine _Learning Day 7.pdf
14.9 MB
1.1 Machine _Learning Day 1.pdf
13.5 MB
5.1 Machine _Learning Day 5.pdf
12.0 MB
2.1 Machine _Learning Day 2.pdf
8.2 MB
10.1 Machine _Learning - 9B.pdf
7.7 MB
9.1 Machine _Learning 9A.pdf
6.2 MB
14.1 Machine _Learning - 13.pdf
4.4 MB
19.2 Machine _Learning - 18.pdf
4.0 MB
15.2 Machine _Learning - 14.pdf
3.5 MB
19.3 Seaborn.ipynb
2.5 MB
12.1 images in pdf.pdf
2.0 MB
21.2 LendingClub.ipynb
1.6 MB
15.1 Machine _Learning - 14 - Practical.pdf
1.3 MB
14.2 Practicals.zip
1.2 MB
18.1 Machine _Learning - 17 - Practical.pdf
1.2 MB
13.1 images in pdf.pdf
1.0 MB
16.1 Machine _Learning - 15 - Practical.pdf
1.0 MB
6.2 Z Table 20210801.pdf
894.5 kB
19.1 Machine _Learning - 18 - Practical.pdf
418.5 kB
17.1 Machine _Learning - 16 - Practical.pdf
358.0 kB
21.3 Machine _Learning - 19 B - Practical.pdf
252.9 kB
22. Day 20 A - EDA Cont.srt
220.5 kB
8. Day 8 - Statistics for Data Analysis - Statistical Hypothesis.srt
215.9 kB
19. Day 18 - Seaborn.srt
207.8 kB
3. Day 3 - Statistics for Data Analysis - Scalar, Vectors and Matrix.srt
202.4 kB
6. Day 6 - Statistics for Data Analysis - Probability.srt
201.6 kB
14. Day 13 - Numpy.srt
201.1 kB
18. Day 17 - Pandas.srt
188.2 kB
17. Day 16 - Pandas.srt
184.8 kB
15. Day 14 - Pandas.srt
178.5 kB
12. Day 11 - Python for Data Analysis.srt
177.8 kB
11. Day 10 - Python for Data Analysis.srt
171.9 kB
13. Day 12 - Python for Data Analysis.srt
169.8 kB
4. Day 4 - Statistics for Data Analysis - Probability.srt
167.3 kB
5. Day 5 - Statistics for Data Analysis - Probability.srt
166.1 kB
1. Day 1 - Introduction to Data Science.srt
164.6 kB
7. Day 7 - Statistics for Data Analysis - Probability.srt
163.5 kB
10. Day 9B - Python for Data Analysis.srt
150.9 kB
2. Day 2 - Introduction to Data Analytics.srt
150.3 kB
16. Day 15 - Pandas.srt
122.8 kB
20. Day 19 A - Seaborn.srt
102.1 kB
15.3 Pandas practicals.zip
72.8 kB
21. Day 19 B - EDA.srt
61.7 kB
9. Day 9A - Statistics for Data Analysis - Statistical Hypothesis.srt
44.6 kB
23. Day 20 B - What Next.srt
35.4 kB
11.1 Python Notebook.zip
34.2 kB
7.2 Reference Links.txt
284 Bytes
21.1 EDA Data .txt
84 Bytes
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