Threshold to the AI Multiverse
In the vast AI cosmos, knowledge scatters like stardust, leaving seekers lost in the cosmic expanse. While the journey of self-discovery and learning from mistakes is valuable, the AI universe evolves rapidly. To keep you up to date and provide a smooth path from AI novice to expert, we've forged an AI Portal Gun. It teleports you to precisely the right planet in this ever-changing universe, offering a comprehensive voyage from AI fundamentals to advanced frontiers.
We'll teleport you to the planet where a curated collection of free tutorials, guides, articles, courses, and books awaits. These resources are designed to unravel complex concepts and empower you with the skills to thrive in the ML multiverse.
Whether your passion aligns with computer vision, natural language processing, reinforcement learning, deep learning, or any machine learning facet, you'll find abundant, tailored resources. You'll also delve deep into AI applications in healthcare and robotics, and embark on a profound exploration of generative AI, spanning audio, video, images, and code generation. Plus, uncover the mathematics behind AI's core principles.
Our mission extends beyond information provision; we aim to cultivate a supportive community of learners inspiring each other on this exhilarating journey.
How to navigate AI Cosmos
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Browse Our Catalog: Explore our extensive library of ML resources. Begin your exploration with our comprehensive courses. Subsequently, dive into a wealth of resources, including explainers (videos), articles, research papers, books, notebooks and more.
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Choose Your Path: Whether you're a beginner or an experienced practitioner, we have resources tailored to your domain. Select the courses that align with your goals and expertise level.
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Open Source, Open Access: All our content is open source and freely accessible. No paywalls, just knowledge waiting to be explored.
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Join Our Community: Connect with fellow learners and mentors on our Discord server (opens in a new tab). Discuss concepts, ask questions, and collaborate on ML projects through our vibrant community.
Contribute to Our Knowledge Base
This course is open source, allowing anyone to view the code. You can contribute by adding new resources, courses, posts, or even enhancing existing content on our GitHub repository (opens in a new tab).
Help us expand and enhance the learning experience for everyone. Your contribution counts!
Feedback
Your feedback is the cornerstone of this guide! Whether you have queries, thoughts, or creative suggestions, we welcome them all. Let's make this learning experience even more awesome together; connect with us through:
- Make an issue on GitHub (opens in a new tab)
- Email us at openmlguide@gmail.com
- Join our Discord community (opens in a new tab)
- Follow us on Twitter (opens in a new tab)
Consider your feedback as the algorithmic tweak that fine-tunes our ML guide for maximum awesomeness. Your thoughts are the code to an upgraded learning experience.
Special Thanks
Our heartfelt 💚 gratitude Stanford Online (opens in a new tab), MIT OpenCourseWare (opens in a new tab), DeepLearning AI (opens in a new tab), Fast.AI (opens in a new tab), 3Blue1Brown (opens in a new tab), Hugging Face (opens in a new tab), Coursera (opens in a new tab) and many others for their unwavering commitment to education and dedication to making high-quality resources accessible to all.