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[CourseClub.Me] O'REILLY - Python for Data Science Complete Video Course Video Training
magnet:?xt=urn:btih:a8c15cdfd9b2b16a7a39ce1904cffa9d506d0eb2&dn=[CourseClub.Me] O'REILLY - Python for Data Science Complete Video Course Video Training
磁力链接详情
Hash值:
a8c15cdfd9b2b16a7a39ce1904cffa9d506d0eb2
点击数:
267
文件大小:
13.13 GB
文件数量:
89
创建日期:
2020-2-9 16:20
最后访问:
2024-10-3 05:58
访问标签:
CourseClub
Me
O'REILLY
-
Python
for
Data
Science
Complete
Video
Course
Video
Training
文件列表详情
01 - Python for Data Science Complete Video Course Video Training - Introduction.mp4 76.64 MB
02 - Learning objectives.mp4 11.21 MB
03 - 1.1 History of Python in data science.mp4 78.08 MB
04 - 1.2 Overview of Python data science libraries.mp4 44.37 MB
05 - 1.3 Future trends of Python in AI, ML, and data science.mp4 77.54 MB
06 - Learning objectives.mp4 25 MB
07 - 2.1 Create your first Colab document.mp4 328.82 MB
08 - 2.2 Manage Colab documents.mp4 451.8 MB
09 - 2.3 Use magic functions.mp4 156.26 MB
10 - 2.4 Understand compatibility with Jupyter.mp4 258.05 MB
11 - Learning objectives.mp4 28.81 MB
12 - 3.1 Write procedural code.mp4 112.86 MB
13 - 3.2 Use simple expressions and variables.mp4 173.93 MB
14 - 3.3 Work with the built-in types.mp4 66.6 MB
15 - 3.4 Learn to Print.mp4 70.6 MB
16 - 3.5 Perform basic math operations.mp4 167.11 MB
17 - 3.6 Use classes and objects with dot notation.mp4 194.46 MB
18 - Learning objectives.mp4 17 MB
19 - 4.1 Use string methods.mp4 131.93 MB
20 - 4.2 Format strings.mp4 98.69 MB
21 - 4.3 Manipulate strings - membership, slicing, and concatenation.mp4 136.75 MB
22 - 4.4 Learn to use unicode.mp4 74.37 MB
23 - Learning objectives.mp4 22.45 MB
24 - 5.1 Use lists and tuples.mp4 369.96 MB
25 - 5.2 Explore dictionaries.mp4 213.33 MB
26 - 5.3 Dive into sets.mp4 83.03 MB
27 - 5.4 Work with the numpy array.mp4 234.44 MB
28 - 5.5 Use the Pandas DataFrame.mp4 116.78 MB
29 - 5.6 Use the Pandas Series.mp4 71.62 MB
30 - Learning objectives.mp4 24 MB
31 - 6.1 Convert lists to dicts and back.mp4 74.45 MB
32 - 6.2 Convert dicts to Pandas Dataframe.mp4 104.57 MB
33 - 6.3 Convert characters to integers and back.mp4 35.73 MB
34 - 6.4 Convert between hexadecimal, binary, and floats.mp4 101.36 MB
35 - Learning objectives.mp4 24.93 MB
36 - 7.1 Learn to loop with for loops.mp4 44.92 MB
37 - 7.2 Repeat with while loops.mp4 50.23 MB
38 - 7.3 Learn to handle exceptions.mp4 111.94 MB
39 - 7.4 Use conditionals.mp4 168.25 MB
40 - Learning objectives.mp4 22.46 MB
41 - 8.1 Write and use functions.mp4 206.47 MB
42 - 8.2 Learn to use decorators.mp4 210.94 MB
43 - 8.3 Compose closure functions.mp4 132.86 MB
44 - 8.4 Use lambdas.mp4 106.23 MB
45 - 8.5 Advanced Use of Functions.mp4 319.02 MB
46 - Learning objectives.mp4 33.79 MB
47 - 9.1 Learn NumPy.mp4 287.95 MB
48 - 9.2 Learn SciPy.mp4 664.99 MB
49 - 9.3 Learn Pandas.mp4 335.61 MB
50 - 9.4 Learn TensorFlow.mp4 341.9 MB
51 - 9.5 Use Seaborn for 2D plots.mp4 261.65 MB
52 - 9.6 Use Plotly for interactive plots.mp4 262.06 MB
53 - 9.7 Specialized Visualization Libraries.mp4 241.69 MB
54 - 9.8 Learn Natural Language Processing Libraries.mp4 124.95 MB
55 - Learning objectives.mp4 27.7 MB
56 - 10.1 Understand functional programming.mp4 151.13 MB
57 - 10.2 Apply functions to data science workflows.mp4 47.12 MB
58 - 10.3 Use map_reduce_filter.mp4 95.23 MB
59 - 10.4 Use list comprehensions.mp4 98.27 MB
60 - 10.5 Use dictionary comprehensions.mp4 15.45 MB
61 - Learning objectives.mp4 17.83 MB
62 - 11.1 Use generators.mp4 69.4 MB
63 - 11.2 Design generator pipelines.mp4 141.25 MB
64 - 11.3 Implement lazy evaluation functions.mp4 59.14 MB
65 - Learning objectives.mp4 20.97 MB
66 - 12.1 Perform simple pattern matching.mp4 97.05 MB
67 - 12.2 Use regular expressions.mp4 284.59 MB
68 - 12.3 Learn text processing techniques - Beautiful Soup.mp4 87.6 MB
69 - Learning objectives.mp4 18.2 MB
70 - 13.1 Sort in Python.mp4 186.66 MB
71 - 13.2 Create custom sorting functions.mp4 229.33 MB
72 - 13.3 Sort in Pandas.mp4 301.95 MB
73 - Learning objectives.mp4 22.1 MB
74 - 14.1 Read and write files - file, pickle, CSV, JSON.mp4 214.71 MB
75 - 14.2 Read and write with Pandas - CSV, JSON.mp4 336.5 MB
76 - 14.3 Read and write using web resources (requests, boto, github).mp4 110.86 MB
77 - 14.4 Use function-based concurrency.mp4 608.14 MB
78 - Learning objectives.mp4 20.91 MB
79 - 15.1 Share with Github.mp4 358.09 MB
80 - 15.2 Create Kaggle Kernels.mp4 207.48 MB
81 - 15.3 Collaborate with Colab.mp4 125.18 MB
82 - 15.4 Post public graphs with Plotly.mp4 103.5 MB
83 - Learning Objectives.mp4 28.71 MB
84 - 16.1 PyTest.mp4 372.92 MB
85 - 16.2 Visual Studio Code.mp4 364.64 MB
86 - 16.3 Vim.mp4 136.81 MB
87 - 16.4 Ludwig (Open Source AutoML).mp4 146.48 MB
88 - 16.5 Sklearn Algorithm Cheatsheet.mp4 104.05 MB
89 - 16.6 Recommendations.mp4 47.75 MB
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