Complete Python Course - Modules & Packages
shravan andoria
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Complete Python Course - Modules & Packages
56 просмотров · 8 дн. назад
shravan andoria
53 подписчика
56 просмотров · 8 дн. назад
In this video, we dive into *Python Modules and Packages* and learn how they help us organize, reuse, and manage Python code effectively.
If you're learning Python for **Machine Learning, Data Science, AI, or Software Development**, understanding modules and packages is an essential foundation.
📚 What You'll Learn in This Video
What are Python modules and packages?
How to import Python modules
Using `import` and `from ... import`
Importing specific functions and variables
Using `*` while importing
Working with built-in Python libraries
Installing and using external packages with `pip`
Understanding `requirements.txt`
Creating your own Python package
Creating and using your own modules
Creating sub-packages inside packages
Using `__init__.py`
Importing functions from custom packages
Working with NumPy
Working with the `math` module
Generating random numbers with the `random` module
Using `os` for operating-system-related tasks
Working with files using `shutil`
Converting Python dictionaries to JSON and vice versa
Reading and writing CSV files
Working with dates and times using `datetime`
Using `time.sleep()`
Introduction to Regular Expressions with `re`
Practical examples and exercises to practice on your own
Throughout the video, we use *hands-on Python examples* so you can understand not just the syntax, but also where these modules and packages are useful in real projects.
💻 Course GitHub Repository
You can find the code and resources for this Machine Learning course here:
https://github.com/shravanandoria/mac...
Make sure to practice the examples yourself and experiment with different Python libraries. The more you work with modules and packages, the easier it becomes to structure larger Python projects.
If you found this video helpful, *like the video, subscribe to the channel, and turn on notifications* for more videos on Python, Machine Learning, AI, and practical ML projects.
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