[FreeCoursesOnline.Me] O'REILLY - Python for Data Science Complete Video Course Video Training

• [FreeCoursesOnline.Me] O'REILLY - Python for Data Science Complete Video Course Video Training
• 0. Websites you may like/How you can help Team-FTU.txt 237 B
• 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

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