CourseClub Me REILLY Python for Data Science Complete Video Course Video Training

CourseClub Me REILLY Python for Data Science Complete Video Course Video Training

Name	[CourseClub.Me] O'REILLY - Python for Data Science Complete Video Course Video Training	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	14.1 GB
Total Files	91
Hash	A8C15CDFD9B2B16A7A39CE1904CFFA9D506D0EB2

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01 - Python for Data Science Complete Video Course Video Training - Introduction.mp4	80.4 MB
02 - Learning objectives.mp4	11.8 MB
03 - 1.1 History of Python in data science.mp4	81.9 MB
04 - 1.2 Overview of Python data science libraries.mp4	46.5 MB
05 - 1.3 Future trends of Python in AI, ML, and data science.mp4	81.3 MB
06 - Learning objectives.mp4	26.2 MB
07 - 2.1 Create your first Colab document.mp4	344.8 MB
08 - 2.2 Manage Colab documents.mp4	473.7 MB
09 - 2.3 Use magic functions.mp4	163.8 MB
10 - 2.4 Understand compatibility with Jupyter.mp4	270.6 MB
11 - Learning objectives.mp4	30.2 MB
12 - 3.1 Write procedural code.mp4	118.3 MB
13 - 3.2 Use simple expressions and variables.mp4	182.4 MB
14 - 3.3 Work with the built-in types.mp4	69.8 MB
15 - 3.4 Learn to Print.mp4	74.0 MB
16 - 3.5 Perform basic math operations.mp4	175.2 MB
17 - 3.6 Use classes and objects with dot notation.mp4	203.9 MB
18 - Learning objectives.mp4	17.8 MB
19 - 4.1 Use string methods.mp4	138.3 MB
20 - 4.2 Format strings.mp4	103.5 MB
21 - 4.3 Manipulate strings - membership, slicing, and concatenation.mp4	143.4 MB
22 - 4.4 Learn to use unicode.mp4	78.0 MB
23 - Learning objectives.mp4	23.5 MB
24 - 5.1 Use lists and tuples.mp4	387.9 MB
25 - 5.2 Explore dictionaries.mp4	223.7 MB
26 - 5.3 Dive into sets.mp4	87.1 MB
27 - 5.4 Work with the numpy array.mp4	245.8 MB
28 - 5.5 Use the Pandas DataFrame.mp4	122.5 MB
29 - 5.6 Use the Pandas Series.mp4	75.1 MB
30 - Learning objectives.mp4	25.2 MB
31 - 6.1 Convert lists to dicts and back.mp4	78.1 MB
32 - 6.2 Convert dicts to Pandas Dataframe.mp4	109.6 MB
33 - 6.3 Convert characters to integers and back.mp4	37.5 MB
34 - 6.4 Convert between hexadecimal, binary, and floats.mp4	106.3 MB
35 - Learning objectives.mp4	26.1 MB
36 - 7.1 Learn to loop with for loops.mp4	47.1 MB
37 - 7.2 Repeat with while loops.mp4	52.7 MB
38 - 7.3 Learn to handle exceptions.mp4	117.4 MB
39 - 7.4 Use conditionals.mp4	176.4 MB
40 - Learning objectives.mp4	23.5 MB
41 - 8.1 Write and use functions.mp4	216.5 MB
42 - 8.2 Learn to use decorators.mp4	221.2 MB
43 - 8.3 Compose closure functions.mp4	139.3 MB
44 - 8.4 Use lambdas.mp4	111.4 MB
45 - 8.5 Advanced Use of Functions.mp4	334.5 MB
46 - Learning objectives.mp4	35.4 MB
47 - 9.1 Learn NumPy.mp4	301.9 MB
48 - 9.2 Learn SciPy.mp4	697.3 MB
49 - 9.3 Learn Pandas.mp4	351.9 MB
50 - 9.4 Learn TensorFlow.mp4	358.5 MB
51 - 9.5 Use Seaborn for 2D plots.mp4	274.4 MB
52 - 9.6 Use Plotly for interactive plots.mp4	274.8 MB
53 - 9.7 Specialized Visualization Libraries.mp4	253.4 MB
54 - 9.8 Learn Natural Language Processing Libraries.mp4	131.0 MB
55 - Learning objectives.mp4	29.0 MB
56 - 10.1 Understand functional programming.mp4	158.5 MB
57 - 10.2 Apply functions to data science workflows.mp4	49.4 MB
58 - 10.3 Use map_reduce_filter.mp4	99.9 MB
59 - 10.4 Use list comprehensions.mp4	103.0 MB
60 - 10.5 Use dictionary comprehensions.mp4	16.2 MB
61 - Learning objectives.mp4	18.7 MB
62 - 11.1 Use generators.mp4	72.8 MB
63 - 11.2 Design generator pipelines.mp4	148.1 MB
64 - 11.3 Implement lazy evaluation functions.mp4	62.0 MB
65 - Learning objectives.mp4	22.0 MB
66 - 12.1 Perform simple pattern matching.mp4	101.8 MB
67 - 12.2 Use regular expressions.mp4	298.4 MB
68 - 12.3 Learn text processing techniques - Beautiful Soup.mp4	91.9 MB
69 - Learning objectives.mp4	19.1 MB
70 - 13.1 Sort in Python.mp4	195.7 MB
71 - 13.2 Create custom sorting functions.mp4	240.5 MB
72 - 13.3 Sort in Pandas.mp4	316.6 MB
73 - Learning objectives.mp4	23.2 MB
74 - 14.1 Read and write files - file, pickle, CSV, JSON.mp4	225.1 MB
75 - 14.2 Read and write with Pandas - CSV, JSON.mp4	352.8 MB
76 - 14.3 Read and write using web resources (requests, boto, github).mp4	116.2 MB
77 - 14.4 Use function-based concurrency.mp4	637.7 MB
78 - Learning objectives.mp4	21.9 MB
79 - 15.1 Share with Github.mp4	375.5 MB
80 - 15.2 Create Kaggle Kernels.mp4	217.6 MB
81 - 15.3 Collaborate with Colab.mp4	131.3 MB
82 - 15.4 Post public graphs with Plotly.mp4	108.5 MB
83 - Learning Objectives.mp4	30.1 MB
84 - 16.1 PyTest.mp4	391.0 MB
85 - 16.2 Visual Studio Code.mp4	382.4 MB
86 - 16.3 Vim.mp4	143.5 MB
87 - 16.4 Ludwig (Open Source AutoML).mp4	153.6 MB
88 - 16.5 Sklearn Algorithm Cheatsheet.mp4	109.1 MB
89 - 16.6 Recommendations.mp4	50.1 MB
[CourseClub.Me].url	0.0 KB
[DesireCourse.Net].url	0.1 KB
Total files 91