Torrent Info
Title [FreeCoursesOnline.Me] O'REILLY - Python for Data Science Complete Video Course Video Training
Category
Size 13.13GB

Files List
Please note that this page does not hosts or makes available any of the listed filenames. You cannot download any of those files from here.
01 - Python for Data Science Complete Video Course Video Training - Introduction.mp4 76.64MB
02 - Learning objectives.mp4 11.21MB
03 - 1.1 History of Python in data science.mp4 78.08MB
04 - 1.2 Overview of Python data science libraries.mp4 44.37MB
05 - 1.3 Future trends of Python in AI, ML, and data science.mp4 77.54MB
06 - Learning objectives.mp4 25.00MB
07 - 2.1 Create your first Colab document.mp4 328.82MB
08 - 2.2 Manage Colab documents.mp4 451.80MB
09 - 2.3 Use magic functions.mp4 156.26MB
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10 - 2.4 Understand compatibility with Jupyter.mp4 258.05MB
11 - Learning objectives.mp4 28.81MB
12 - 3.1 Write procedural code.mp4 112.86MB
13 - 3.2 Use simple expressions and variables.mp4 173.93MB
14 - 3.3 Work with the built-in types.mp4 66.60MB
15 - 3.4 Learn to Print.mp4 70.60MB
16 - 3.5 Perform basic math operations.mp4 167.11MB
17 - 3.6 Use classes and objects with dot notation.mp4 194.46MB
18 - Learning objectives.mp4 17.00MB
19 - 4.1 Use string methods.mp4 131.93MB
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20 - 4.2 Format strings.mp4 98.69MB
21 - 4.3 Manipulate strings - membership, slicing, and concatenation.mp4 136.75MB
22 - 4.4 Learn to use unicode.mp4 74.37MB
23 - Learning objectives.mp4 22.45MB
24 - 5.1 Use lists and tuples.mp4 369.96MB
25 - 5.2 Explore dictionaries.mp4 213.33MB
26 - 5.3 Dive into sets.mp4 83.03MB
27 - 5.4 Work with the numpy array.mp4 234.44MB
28 - 5.5 Use the Pandas DataFrame.mp4 116.78MB
29 - 5.6 Use the Pandas Series.mp4 71.62MB
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30 - Learning objectives.mp4 24.00MB
31 - 6.1 Convert lists to dicts and back.mp4 74.45MB
32 - 6.2 Convert dicts to Pandas Dataframe.mp4 104.57MB
33 - 6.3 Convert characters to integers and back.mp4 35.73MB
34 - 6.4 Convert between hexadecimal, binary, and floats.mp4 101.36MB
35 - Learning objectives.mp4 24.93MB
36 - 7.1 Learn to loop with for loops.mp4 44.92MB
37 - 7.2 Repeat with while loops.mp4 50.23MB
38 - 7.3 Learn to handle exceptions.mp4 111.94MB
39 - 7.4 Use conditionals.mp4 168.25MB
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40 - Learning objectives.mp4 22.46MB
41 - 8.1 Write and use functions.mp4 206.47MB
42 - 8.2 Learn to use decorators.mp4 210.94MB
43 - 8.3 Compose closure functions.mp4 132.86MB
44 - 8.4 Use lambdas.mp4 106.23MB
45 - 8.5 Advanced Use of Functions.mp4 319.02MB
46 - Learning objectives.mp4 33.79MB
47 - 9.1 Learn NumPy.mp4 287.95MB
48 - 9.2 Learn SciPy.mp4 664.99MB
49 - 9.3 Learn Pandas.mp4 335.61MB
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50 - 9.4 Learn TensorFlow.mp4 341.90MB
51 - 9.5 Use Seaborn for 2D plots.mp4 261.65MB
52 - 9.6 Use Plotly for interactive plots.mp4 262.06MB
53 - 9.7 Specialized Visualization Libraries.mp4 241.69MB
54 - 9.8 Learn Natural Language Processing Libraries.mp4 124.95MB
55 - Learning objectives.mp4 27.70MB
56 - 10.1 Understand functional programming.mp4 151.13MB
57 - 10.2 Apply functions to data science workflows.mp4 47.12MB
58 - 10.3 Use map_reduce_filter.mp4 95.23MB
59 - 10.4 Use list comprehensions.mp4 98.27MB
60 - 10.5 Use dictionary comprehensions.mp4 15.45MB
61 - Learning objectives.mp4 17.83MB
62 - 11.1 Use generators.mp4 69.40MB
63 - 11.2 Design generator pipelines.mp4 141.25MB
64 - 11.3 Implement lazy evaluation functions.mp4 59.14MB
65 - Learning objectives.mp4 20.97MB
66 - 12.1 Perform simple pattern matching.mp4 97.05MB
67 - 12.2 Use regular expressions.mp4 284.59MB
68 - 12.3 Learn text processing techniques - Beautiful Soup.mp4 87.60MB
69 - Learning objectives.mp4 18.20MB
70 - 13.1 Sort in Python.mp4 186.66MB
71 - 13.2 Create custom sorting functions.mp4 229.33MB
72 - 13.3 Sort in Pandas.mp4 301.95MB
73 - Learning objectives.mp4 22.10MB
74 - 14.1 Read and write files - file, pickle, CSV, JSON.mp4 214.71MB
75 - 14.2 Read and write with Pandas - CSV, JSON.mp4 336.50MB
76 - 14.3 Read and write using web resources (requests, boto, github).mp4 110.86MB
77 - 14.4 Use function-based concurrency.mp4 608.14MB
78 - Learning objectives.mp4 20.91MB
79 - 15.1 Share with Github.mp4 358.09MB
80 - 15.2 Create Kaggle Kernels.mp4 207.48MB
81 - 15.3 Collaborate with Colab.mp4 125.18MB
82 - 15.4 Post public graphs with Plotly.mp4 103.50MB
83 - Learning Objectives.mp4 28.71MB
84 - 16.1 PyTest.mp4 372.92MB
85 - 16.2 Visual Studio Code.mp4 364.64MB
86 - 16.3 Vim.mp4 136.81MB
87 - 16.4 Ludwig (Open Source AutoML).mp4 146.48MB
88 - 16.5 Sklearn Algorithm Cheatsheet.mp4 104.05MB
89 - 16.6 Recommendations.mp4 47.75MB
How you can help Team-FTU.txt 237B
Distribution statistics by country
Singapore (SG) 1
India (IN) 1
Netherlands (NL) 1
Turkey (TR) 1
China (CN) 1
Total 5
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