| 01 - Python for Data Science Complete Video Course Video Training - Introduction.mp4 | 76.6 MB | ||
| 02 - Learning objectives.mp4 | 11.2 MB | ||
| 03 - 1.1 History of Python in data science.mp4 | 78.1 MB | ||
| 04 - 1.2 Overview of Python data science libraries.mp4 | 44.4 MB | ||
| 05 - 1.3 Future trends of Python in AI, ML, and data science.mp4 | 77.5 MB | ||
| 06 - Learning objectives.mp4 | 25 MB | ||
| 07 - 2.1 Create your first Colab document.mp4 | 328.8 MB | ||
| 08 - 2.2 Manage Colab documents.mp4 | 451.8 MB | ||
| 09 - 2.3 Use magic functions.mp4 | 156.3 MB | ||
| 10 - 2.4 Understand compatibility with Jupyter.mp4 | 258.1 MB | ||
| 11 - Learning objectives.mp4 | 28.8 MB | ||
| 12 - 3.1 Write procedural code.mp4 | 112.9 MB | ||
| 13 - 3.2 Use simple expressions and variables.mp4 | 173.9 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 | 167.1 MB | ||
| 17 - 3.6 Use classes and objects with dot notation.mp4 | 194.5 MB | ||
| 18 - Learning objectives.mp4 | 17 MB | ||
| 19 - 4.1 Use string methods.mp4 | 131.9 MB | ||
| 20 - 4.2 Format strings.mp4 | 98.7 MB | ||
| 21 - 4.3 Manipulate strings - membership, slicing, and concatenation.mp4 | 136.7 MB | ||
| 22 - 4.4 Learn to use unicode.mp4 | 74.4 MB | ||
| 23 - Learning objectives.mp4 | 22.5 MB | ||
| 24 - 5.1 Use lists and tuples.mp4 | 370 MB | ||
| 25 - 5.2 Explore dictionaries.mp4 | 213.3 MB | ||
| 26 - 5.3 Dive into sets.mp4 | 83 MB | ||
| 27 - 5.4 Work with the numpy array.mp4 | 234.4 MB | ||
| 28 - 5.5 Use the Pandas DataFrame.mp4 | 116.8 MB | ||
| 29 - 5.6 Use the Pandas Series.mp4 | 71.6 MB | ||
| 30 - Learning objectives.mp4 | 24 MB | ||
| 31 - 6.1 Convert lists to dicts and back.mp4 | 74.4 MB | ||
| 32 - 6.2 Convert dicts to Pandas Dataframe.mp4 | 104.6 MB | ||
| 33 - 6.3 Convert characters to integers and back.mp4 | 35.7 MB | ||
| 34 - 6.4 Convert between hexadecimal, binary, and floats.mp4 | 101.4 MB | ||
| 35 - Learning objectives.mp4 | 24.9 MB | ||
| 36 - 7.1 Learn to loop with for loops.mp4 | 44.9 MB | ||
| 37 - 7.2 Repeat with while loops.mp4 | 50.2 MB | ||
| 38 - 7.3 Learn to handle exceptions.mp4 | 111.9 MB | ||
| 39 - 7.4 Use conditionals.mp4 | 168.2 MB | ||
| 40 - Learning objectives.mp4 | 22.5 MB | ||
| 41 - 8.1 Write and use functions.mp4 | 206.5 MB | ||
| 42 - 8.2 Learn to use decorators.mp4 | 210.9 MB | ||
| 43 - 8.3 Compose closure functions.mp4 | 132.9 MB | ||
| 44 - 8.4 Use lambdas.mp4 | 106.2 MB | ||
| 45 - 8.5 Advanced Use of Functions.mp4 | 319 MB | ||
| 46 - Learning objectives.mp4 | 33.8 MB | ||
| 47 - 9.1 Learn NumPy.mp4 | 287.9 MB | ||
| 48 - 9.2 Learn SciPy.mp4 | 665 MB | ||
| 49 - 9.3 Learn Pandas.mp4 | 335.6 MB | ||
| 50 - 9.4 Learn TensorFlow.mp4 | 341.9 MB | ||
| 51 - 9.5 Use Seaborn for 2D plots.mp4 | 261.6 MB | ||
| 52 - 9.6 Use Plotly for interactive plots.mp4 | 262.1 MB | ||
| 53 - 9.7 Specialized Visualization Libraries.mp4 | 241.7 MB | ||
| 54 - 9.8 Learn Natural Language Processing Libraries.mp4 | 124.9 MB | ||
| 55 - Learning objectives.mp4 | 27.7 MB | ||
| 56 - 10.1 Understand functional programming.mp4 | 151.1 MB | ||
| 57 - 10.2 Apply functions to data science workflows.mp4 | 47.1 MB | ||
| 58 - 10.3 Use map_reduce_filter.mp4 | 95.2 MB | ||
| 59 - 10.4 Use list comprehensions.mp4 | 98.3 MB | ||
| 60 - 10.5 Use dictionary comprehensions.mp4 | 15.4 MB | ||
| 61 - Learning objectives.mp4 | 17.8 MB | ||
| 62 - 11.1 Use generators.mp4 | 69.4 MB | ||
| 63 - 11.2 Design generator pipelines.mp4 | 141.3 MB | ||
| 64 - 11.3 Implement lazy evaluation functions.mp4 | 59.1 MB | ||
| 65 - Learning objectives.mp4 | 21 MB | ||
| 66 - 12.1 Perform simple pattern matching.mp4 | 97.1 MB | ||
| 67 - 12.2 Use regular expressions.mp4 | 284.6 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 | 186.7 MB | ||
| 71 - 13.2 Create custom sorting functions.mp4 | 229.3 MB | ||
| 72 - 13.3 Sort in Pandas.mp4 | 302 MB | ||
| 73 - Learning objectives.mp4 | 22.1 MB | ||
| 74 - 14.1 Read and write files - file, pickle, CSV, JSON.mp4 | 214.7 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 | 110.9 MB | ||
| 77 - 14.4 Use function-based concurrency.mp4 | 608.1 MB | ||
| 78 - Learning objectives.mp4 | 20.9 MB | ||
| 79 - 15.1 Share with Github.mp4 | 358.1 MB | ||
| 80 - 15.2 Create Kaggle Kernels.mp4 | 207.5 MB | ||
| 81 - 15.3 Collaborate with Colab.mp4 | 125.2 MB | ||
| 82 - 15.4 Post public graphs with Plotly.mp4 | 103.5 MB | ||
| 83 - Learning Objectives.mp4 | 28.7 MB | ||
| 84 - 16.1 PyTest.mp4 | 372.9 MB | ||
| 85 - 16.2 Visual Studio Code.mp4 | 364.6 MB | ||
| 86 - 16.3 Vim.mp4 | 136.8 MB | ||
| 87 - 16.4 Ludwig (Open Source AutoML).mp4 | 146.5 MB | ||
| 88 - 16.5 Sklearn Algorithm Cheatsheet.mp4 | 104.1 MB | ||
| 89 - 16.6 Recommendations.mp4 | 47.7 MB | ||
| [CourseClub.Me].url | 0 B | ||
| [DesireCourse.Net].url | 0 B | ||
| ▲ 91 total files | |||
[O’REILLY] Python for Data Science Complete Video Course Video Training
While there are resources for Data Science and resources for Machine Learning, there’s a distinct gap in resources for the precursor course to Data Science and Machine Learning.
For More Courses Visit: https://desirecourse.net
For More Courses Visit: https://courseclub.me
| torrent name | size | uploader | age | seed | leech |
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| 5.5 GB | notimmune | 8 months | 14 | 4 | |
| 1.1 GB | notimmune | 1 year | 3 | 1 | |
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Ansible From Basics to Guru, 2nd Edition - LiveLessons, Pearson, O'Reilly Media Posted by
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2.5 GB | notimmune | 1 year | 8 | 1 |
| 947.21 MB | Prom3th3uS | 1 year | 2 | 6 | |
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