55 points by trendytechguy 1 year ago flag hide 16 comments
johnsmith 1 year ago next
[HN story title] Ask HN: What are your favorite resources for learning cutting-edge ML techniques? I've been looking for ways to improve my knowledge in machine learning and stay updated with the latest techniques. Would love to hear about the resources that have helped you.
janedoe 1 year ago next
@johnsmith Thanks for the post! I've found the following resources to be helpful: * [Resource 1](https://example.com/resource1) - A comprehensive guide to deep learning * [Resource 2](https://example.com/resource2) - An online course on advanced ML techniques * [Resource 3](https://example.com/resource3) - A collection of up-to-date research papers and articles
aliceprogrammer 1 year ago prev next
@janedoe Thanks for sharing those resources! I've been looking for something like Resource 2. I'll check them out. Anyone else have any recommendations?
bobbuilder 1 year ago prev next
I would recommend checking out the open-source project [X-ML](https://github.com/example-org/x-ml) - it's a collection of curated implementations of various ML algorithms and techniques. Their documentation is very well-written and easy to follow.
charliebuilds 1 year ago next
@bobbuilder Thanks for sharing! I've seen that project before but it's been a while since I took a look at it. Looking forward to checking it out again. I appreciate the recommendation.
dev1 1 year ago prev next
I've also found these newsletters/blogs to be very useful in staying updated on new ML techniques: * [ML Weekly](https://mlweekly.org) - A weekly newsletter with a curated list of new ML papers, tools, and frameworks * [Adam Geitgey's Blog](https://adgefforts.com) - Great articles on various ML topics, often explaining cutting-edge techniques in non-technical terms
evelyndeveloper 1 year ago next
@dev1 Thanks for sharing! I've subscribed to both ML Weekly and Adam Geitgey's Blog, can't wait to start reading! I've also found the YouTube channel [Data Science Weekly](https://www.youtube.com/c/datascienceweekly) to be a treasure trove of information on new ML techniques and tools.
frederickfang 1 year ago prev next
[Resource 4](https://example.com/resource4) - A list of recommended ML courses and learning paths (Disclaimer: I am the author of this resource)
gracegrowth 1 year ago next
@frederickfang Thanks for sharing, I'll check it out. It's always great to see recommendations from experienced practitioners.
henryhacker 1 year ago prev next
There's a fantastic resource called [Awesome ML-Engineer](https://github.com/maximvedel/awesome-ml-engineer) - it's a curated list of tools for building and deploying ML models. It also links to a number of learning resources and tutorials for ML engineering best practices.
illuminaughty 1 year ago next
@henryhacker Thanks for sharing, I've added it to my bookmarks!
jessicajones 1 year ago prev next
[Resource 5](https://example.com/resource5) - A monthly newsletter that curates a list of the most interesting ML and AI research and applications
justinjoystick 1 year ago next
@jessicajones That's awesome, I'll sign up for the newsletter!
katherinekeyboard 1 year ago prev next
I highly recommend the ML engineering course at [Awesome University](https://awesomeuniversity.com) - it goes over best practices for model training, evaluation, and deployment. I've found it extremely helpful in my career as a machine learning engineer.
lamarlearner 1 year ago next
@katherinekeyboard Thanks for the recommendation, I'll look into it! I'm always looking to improve my skills as a ML engineer.
williamwriter 1 year ago prev next
One more resource I'd like to add to the list is [Applied ML](https://appliedml.org) - a community-driven website for sharing and discussing applied machine learning. Great for learning about new techniques and tools in a practical setting.