Coding-problems contains an updated collection of solutions to numerous coding and algorithmic problems that new program

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The rest of the advanced topics are provided in the intermediate folder, such as writing idiomatic Python, a few other general topics, and some best practices to help you avoid writing disastrous and inefficient code. Not to mention, each topic in the repo does come with plenty of sample code for you to analyze thoroughly, along with exercises to help you track your progress.

The repo Project Based Learning is packed with tutorials for various programming languages with a specific focus on being project-oriented. On visiting his repo, you’ll notice a huge list of over 20 programming languages, we’ll be focussing only on Python for this write-up but feel free to check the projects from other programming languages.

The name Python Reference says it all. Unlike other repositories that focus on providing useful Python tutorials for a seamless learning experience, the python reference repo is more of a collection of various Python topics for intermediate developers. Although we recommend you take a look at the repo for the specifics, a brief overview of the contents of the repo is below:

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Valencia got a weird email from someone claiming to work for an unnamed philanthropist, requesting a call. “For a fairly small organization like ours — we have 15 employees — you become a little suspicious,” he says. “Is this one of those send-money-to-whatever” scams?

There’s also a small section explaining how to use this repository to help you make the most out of this repo. Oleksii calls the repo a playground and a cheat sheet as during the learning phase, learners will often return to the repo to experiment with the code examples for a closer hands-on feel. Once you feel comfortable writing your own Python code, you can use the mentioned linting tools, like pylint, to clean the code while the necessary testing is handled by pytest.

If you’ve been learning Python and want to test your knowledge, we highly suggest you give Jeffrey’s repo a shot before looking for practice exercises anywhere else online. It comes with the required hints and the solution, but try not to scroll too far down, or else you’ll stumble upon the answer.

Once you start following this approach, you’ll be able to cover the entirety of this Python book within a month or two, tops. The repo contains the files you will need to build the book for yourself, or you can simply download the book from his repo, the download links are available there.

If you have already mastered the basics of Python, then this repo might be suitable for you to help you understand a host of advanced topics. The repo provides Jupyter Notebooks for various topics, such as useful regular expressions, Cython with and without IPython, and many more like it, while giving you the flexibility to edit and run the code as you wish.

Similar to learn-python3, learn-python repository also serves as a handy collection of Python resources for beginners and intermediate learners. The repository uses a collection of Python scripts to cover individual topics in Python, such as operators, data types, classes, modules, and much more, with precise explanations and accompanying examples.

It is because if you picked Python intending to get into Machine Learning, this repository presents a crucial step in your Machine Learning journey. Do keep in mind that this repo assumes you already know the core concepts of Python with a bit of introduction to Machine Learning.

First released in March 2018 by João Ventura, full-speed-python is essentially a book that covers the fundamentals of Python along with more advanced topics with a significant emphasis on practical learning. After explaining each topic, João tries to solidify the understanding of the concepts by presenting his readers with sufficient exercises. These exercises play a crucial role in bringing Python learners up to speed with Python’s syntax in a short period.

This GitHub repo contains resources for learning and teaching beginner to intermediate-level Python 3. The contents of this repo are very well structured and in Jupyter Notebooks. The beginner folder inside the notebooks folder contains 19 introductory topics such as strings, conditionals, classes, exceptions, and so, to get you started. We recommend taking a look at the repo for the full list.

This repo covers the various aspects of TensorFlow for Machine Learning in Python, such as all the necessary information related to its introduction, installation, and loads of other valuable resources. These resources include official tutorials, blogs, videos, and much more to help you make the most out of TensorFlow for all your Machine Learning projects and tasks.

Jeffrey Hu’s GitHub repo is a fairly straightforward one. His repo has more than 100 Python programming challenges that cater to new developers, intermediate developers, as well as veteran professionals. Jeffrey also has a website that teaches you foundational Python in the form of comics, which you can also use, but unless you know Chinese, you would be hard-pressed to understand it.