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Home TOP 10

Top 10 Github Repositories For Python Education In 2023

February 8, 2023
Python

The rise in Python’s popularity is a direct result of recent developments in AI. The technological industry is in awe of what AI is capable of and the productivity gains being made there by machine learning. Python programming is used to power a wide range of global businesses, including data research, web development, banking, and security. As a tech skill, demand is steadily rising. Although there are many online resources for learning Python programming, Github repository learning is the preferred method among developers. You can learn Python from a variety of Github repositories online. The top 10 GitHub repositories listed here all have useful tutorials to improve your skills. The top Github repositories listed here will be beneficial for learning Python.

Asabeneh/30 Days of Python
This is regarded as one of the best Github repositories and was created by veteran Python programmer Asabeneh Yetayeh. One of his many repositories for modern programming languages is this one. Beginners will find it difficult to learn Python in just 30 days of coding. It is a step-by-step guide that also covers typical problems. At the end of each course, you receive notes and assignments to use as a student to gauge your comprehension. There are exercises in categories 1-3 to test your understanding of the concepts covered that day. You must actively participate in the 30DaysOfPython challenge in order to receive a certificate.

Vinta/awesome-python
The Awesome Python repository is the second repository on our list of the best GitHub learning repositories for Python that has such astoundingly high statistics. The Awesome Python repository contains a clever and sizable selection of Python frameworks, libraries, tools, and other helpful resources. The repositories offer around 90 different categories for specific projects or topics, including admin panels, data validations, machine vision, algorithms and design patterns, ChatOps tools, and many other themes.

Playground and Cheatsheet for Learning Python
This Python playground was created by Oleksii Trekhleb and others. It provides an interactive interface you can tweak and add code to so you can see how it works. By incorporating numerous steps, the repository encourages you to practise Python programming. You can use the provided Python coding style guides to check the accuracy of your work. This makes it easier to learn Python syntax and expressions through practise. It also improves the quality of your code. Reviewing statements and Python structures can be done using the repository as a reference manual.

Python Project-based learning
This group of programming guides also includes tutorials on Python. More than 100 seasoned software professionals have contributed to it. As a student, you will get experience via tutorials and learn how to build applications from scratch. Students can use a range of projects in the tutorials to practise their Python-based skills. Web scraping, bot development, machine learning, and online apps are some of these. You get to work on real projects and gain in-demand skills.

Python Programming Exercises
Jeffery Hu created this repository for Python difficulties. With the help of the more than 100 Python exercises in the repository, users can evaluate their programming abilities. The exercises involve enjoyable tasks like creating games, using translation software, and manipulating features. Additional comments that are included with the repository describe the requirements and expectations. You can experiment with these examples by using the online IDE that runs in a browser. Jeffrey set up the IDE for those novices experiencing problems setting up a local environment. You can learn a language more quickly if you speak it while reading.

100 Days ML Coding
This practical machine learning course is being taught by Siraj Vajal. It’s a 100-day challenge for machine learning enthusiasts. Siraj breaks down the coursework into daily observations and tasks. You will be introduced to machine-learning subjects during the course of this schedule. The first instructions you’ll read cover topics like installing the proper Python software and tools. Later, you’ll move on to more sophisticated concepts like decision trees and logistic regression. The required datasets and code are provided in the instruction manual for practise.

Practical Python Programming
The fundamentals of Python programming are covered in David Beazily’s course. It puts a lot of focus on script authoring, data processing, and programme organisation. Complete beginners are not intended users of the software. Programmers with prior Python experience are the target audience. This course teaches you how to better understand and use complex Python scripts. To get better at writing, read or modify other developers’ code. It took between 25 to 35 hours of diligent work, including actual coding exercises.

The Algorithms/Python
This repository is the go-to place for Python algorithms. Fundamental algorithms should be mastered by every programmer. There are many Python-based algorithms in it. A collection of programmers who work together on open-source projects is known as a repository. They help one another come up with ideas and solve problems. Collaboration on the documentation and coding of helpful algorithms is their main goal.

The Algorithms
The Algorithms/Python repository is one of the most used and forked Python GitHub repositories for a good reason. This repository provides methods and their implementations for more than 35 categories of Python topics, including data structures, computer vision, linear algebra, neural networks, sorts, and strings, to name a few.

Tensorflow
By making machine learning available to developers on a variety of platforms, including desktop, mobile, IoT, and JavaScript, TensorFlow works wonders in the field. explains the many facets of TensorFlow for Machine Learning in Python, including all the essential details about its introduction, installation, and a wealth of additional useful resources.

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