trybackprop

7 ms·

1. 1.▲
   by trybackprop 1y ago

   A blog for learning all things ML – concepts, interview tips, online ML courses: https://www.trybackprop.com
2. 2.▲
   by trybackprop 2y ago

   I made a list of all the free resources I used to study ML and deep learning to become an ML engineer at FAANG, so I think it'll be helpful to follow these resources: https://www.trybackprop.com/blog/top_ml_learnin
3. 3.▲
   Free ML Resources to Become a FAANG ML Engineer(trybackprop.com)

   2 points by trybackprop 2y ago|1 comments
4. 4.▲
   Build Image Search with Linear Algebra Fundamentals(trybackprop.com)

   3 points by trybackprop 2y ago|1 comments
5. 5.▲
   by trybackprop 2y ago

   I wrote a post about how to build image search using OpenAI's CLIP, and I included a Google Colab notebook that walks you through step by step the coding process. My article also gives the reader all the fundamental linear algebra and
6. 6.▲
   by trybackprop 2y ago

   Thanks for the feedback!
7. 7.▲
   Linear Algebra for AI/ML Part 2 – Dot Product(trybackprop.com)

   2 points by trybackprop 2y ago|3 comments
8. 8.▲
   by trybackprop 2y ago

   From my experience with 5 years in “software engineering” and then 7 years in “machine learning”, what matters is the most is that you like what you do so that you can bring your A game to work. That’ll separate you from the average enginee
9. 9.▲
   Show HN: I created two interactive web experiences to learn ML(trybackprop.com)

   5 points by trybackprop 2y ago|1 comments
10. 10.▲
    by trybackprop 2y ago

    I just posted part 2: https://news.ycombinator.com/item?id=40846513 . It covers the dot product and embeddings and features more visuals and two interactive playgrounds to reinforce the concepts learned. Hope you find it use
11. 11.▲
    by trybackprop 2y ago

    Thanks! I built the interactive playgrounds with React in TypeScript, a lot of SVG manipulation. All of this was built with either Python for visuals or React in general.
12. 12.▲
    Linear Algebra 101 for AI/ML – Dot Product, Embeddings(trybackprop.com)

    9 points by trybackprop 2y ago|6 comments
13. 13.▲
    by trybackprop 2y ago

    Learn the linear algebra you need to know for AI/ML. This covers the dot product both algorithmically and visually and applies it to machine learning embeddings. This article also contains visualizations and two interactive playgrounds
14. 14.▲
    by trybackprop 2y ago

    I actually wrote a blog post about this for experienced software engineers like you who are thinking of transitioning to ML, so I wanted to share it here: https://www.trybackprop.com/blog/2024_06_09_you_dont_need_a_...
15. 15.▲
    PyTorch Documentary Virtual Premiere: Live Stream [video](youtube.com)

    3 points by trybackprop 2y ago|0 comments
16. 16.▲
    by trybackprop 2y ago

    Thank you for the kind words! Please feel free to leave any feedback if you have any. Thanks!
17. 17.▲
    by trybackprop 2y ago

    thank you for the feedback! Ah, I can see how switching from column form to row form right away is confusing, especially if someone isn't familiar with all the notation and the code yet. Same with introducing the tensor method without
18. 18.▲
    by trybackprop 2y ago

    I'm working on this series of articles for folks like you! So glad to hear that you found it useful. Stay tuned for part 2!
19. 19.▲
    by trybackprop 2y ago

    I love 3Blue1Brown's Essence of Linear Algebra series! Yeah, I wrote this article knowing it'd be review for a lot of folks, but I wanted to at least get readers on the same page before diving deeper into the more interesting aspe
20. 20.▲
    by trybackprop 2y ago

    Thank you for the kind words! I currently working on Part 2 of the series (dot products, matrix multiplication, similarity search) and hope to have it out soon. Hope you continue reading!
21. 21.▲
    by trybackprop 2y ago

    Thanks! Part 2 (in the works) will cover visual explanations of the dot product and matrix multiplication, and I'll discuss how to build a visual similarity search engine. Stay tuned!
22. 22.▲
    by trybackprop 2y ago

    Was not expecting to be on the front page of HN! Please feel free to leave feedback on the website (i.e., mobile experience, content, quiz, etc.) Thanks!
23. 23.▲
    Linear Algebra 101 for AI/ML(trybackprop.com)

    79 points by trybackprop 2y ago|14 comments
24. 24.▲
    by trybackprop 2y ago

    Here are three sources: Mistral AI employee: https://x.com/dchaplot/status/1800601722722935153 TechCrunch: https://techcrunch.com/2024/06/11/paris-based-ai-startup-mis... Wall Stree
25. 25.▲
    Mistral AI raises $640M at $6B valuation(generalcatalyst.com)

    115 points by trybackprop 2y ago|60 comments
26. 26.▲
    by trybackprop 2y ago

    It looks like Silicon Valley really values the experience of execs from Instagram: OpenAI CPO: Kevin Weil, Instagram VP of Product 2016-2018 [1] Anthropic CPO: Mike Krieger, Instagram Cofounder and CTO 2010-2018 [2] OpenAI VP Consumer Produ
27. 27.▲
    by trybackprop 2y ago

    +1 the ultra-wide viewing experience is better than what I was expecting: dual monitors
28. 28.▲
    by trybackprop 2y ago

    I select papers based on references from coworkers, Twitter posts by prominent ML researchers I follow, ML podcasts, and results. The research becomes relevant immediately because my team is always looking to incorporate it into our product
29. 29.▲
    by trybackprop 2y ago

    In a given week, I usually do the following: * 15% of my time in technical discussion meetings or 1:1's. Usually discussing ideas around a model, planning, or ML product support * 40% ML development. In the early phase of the project,
30. 30.▲
    by trybackprop 2y ago

    From the blog post: > We observe that with AI-based suggestions, the code author increasingly becomes a reviewer, and it is important to find a balance between the cost of review and added value. We typically address the tradeoff with ac