Confused about Machine Learning? Start Here: 5 Essential GitHub Repositories for Newcomers or Beginners.
1. microsoft/AI-For-Beginners:
- What it is: A comprehensive 12-week program designed specifically for beginners with no prior AI experience.
- What you’ll learn: Covers the essentials of AI, including fundamental concepts like neural networks, deep learning, and computer vision.
- Getting started: This curriculum offers a structured learning path with 26 lessons, 52 quizzes, and various resources like pre- and post-quizzes, written instructions, solutions, assignments, and additional materials.
Link: Microsoft AI For Beginners
2. awesome-machine-learning:
- What it is: More than just a single repository, this is a curated index of various machine learning resources, categorized into different learning aspects.
- What you’ll learn: Explore a vast collection of resources, including machine learning frameworks, libraries, software, tutorials, books, and online courses, allowing you to tailor your learning journey based on your specific interests and preferred learning styles.
- Getting started: Browse the comprehensive list and explore the resources that pique your curiosity. The categorization makes it easy to navigate and find materials relevant to your learning goals.
Link: Awesome Machine Learning
3. Machine-Learning-From-Scratch:
- What it is: This repository delves deeper into the inner workings of machine learning by demonstrating how to implement various models from scratch using Python’s NumPy library.
- What you’ll learn: Gain a deeper understanding of core machine learning algorithms like linear regression, decision trees, and support vector machines by building them from the ground up. This approach provides a strong foundation for comprehending the mechanics behind these algorithms.
- Getting started: Ensure you have a basic understanding of Python and NumPy before diving into this repository. The repository offers explanations and code examples, but some prior programming knowledge is beneficial.
4. mml-book:
- What it is: This repository serves as the companion website for the book “Machine Learning: A Probabilistic Perspective,” offering supplementary materials and resources. The book also offers Mathematical foundations & Examples of machine learning algorithms that use mathematical foundations.
- What you’ll learn: This resource delves into the probabilistic foundations of machine learning, providing a strong theoretical understanding of the underlying concepts behind various algorithms.
- Getting started: While the book itself is not included in the repository, having a solid grasp of basic calculus and probability will be helpful before exploring these materials.
Link: Mathematics For Machine Learning
5. DataTalksClub/machine-learning-zoomcamp:
- What it is: This repository houses the materials from a machine learning Zoomcamp, offering a collection of resources on various machine learning topics.
- What you’ll learn: Access presentations, code examples, and other materials covering diverse subjects within the machine learning domain.
- Getting started: Browse the materials and focus on topics that align with your interests and current understanding. The Zoomcamp recordings might be available elsewhere online, providing additional context and explanation for the presented materials.
Link: DataTalksClub Machine Learning Zoomcamp
These five repositories offer a diverse range of learning opportunities for aspiring machine learning enthusiasts. By exploring these resources, beginners can gain a solid foundation in the fundamentals of AI, delve into specific areas of interest, and build practical skills through hands-on implementation or exploration of curated learning materials. Remember folks, the key to success in this field is consistent learning, exploration, and practice.
