All you need to know about Deep-ML
Deep-ML.com is an open-source machine learning challenge platform designed to help users improve their skills in algorithm development and AI applications. With a range of problems covering fundamental and advanced topics, it's a space for everyone, from beginners to experts, to deepen their understanding and practical skills in machine learning.
Deep-ML is for anyone interested in machine learning, whether you're a student, a data science professional, or an AI enthusiast. Our platform welcomes users from all educational backgrounds and experience levels.
Our platform offers a variety of problems that test different aspects of machine learning. Users can learn through solving real-world problems, and progressively tackle more challenging tasks. Each problem includes explanations, starter code, learn sections, and test cases to help users succeed.
Yes, Deep-ML.com is currently free to use, and we open-source all problems at our GitHub repository.
Absolutely! We encourage open-source contributions. If you're interested in creating or improving problems, you can check out our GitHub repository. Additionally, we're always looking to expand our question base, so feel free to reach out if you'd like to collaborate.
Follow us on Twitter for updates, or join our Discord community. You can also keep an eye on our GitHub page to see our latest open-source developments.
For support or inquiries, you can reach us via email at info@deep-ml.com, or join our Discord server to connect with the community and moderators.
Not quite. While both platforms offer coding challenges, Deep-ML is specifically designed to teach real machine learning skills rather than just algorithmic problem-solving. Our focus is on helping users build a deep understanding of machine learning concepts, from the math to the code, through hands-on problems that mirror real-world applications. Deep-ML is more than a question bank—it's an open-source, community-driven platform where users can learn, collaborate, and develop practical ML skills that are directly applicable to careers in data science and AI.