@yashvi5
1. Python basics 2. Why Machines Learn: Anil Ananthaswamy 3. Andrew Ng ML specialization 4. Andrew Ng Deep learning specialization 5. CS25 Transformer Architecture 6. Andrej Karpathy YT all videos 7. Understanding Deep Learning Simon prince (for theory research top dense work) 8. Numpy/panda/matplotlib/pytorch/tensorflow/jax/sckit learn -> kaggle begginer projects 9. Reading Research paper 10. show ur work & projects (linkedin/blog post/research paper submit)
@mechros4460
I'm a 3rd year undergrad and I second your recommendation of "Understanding Deep Learning". I had an okay understanding of everything, and have even done some research, but diving into this book has been priceless so far.
@asim5546
Hey Boris, thank you so much for this and all your other great videos, they've been really helpful for me so far! ❤ Are you planning on doing a video on the paper implementation part, e.g. your tips on how to start, your own experiences etc?:)
@buckamoona
bored web dev of 9 or so years here, taking on ML is my my goal for this year, so thanks for these videos!
@SM-vz1ek
best advice video about data science that I've seen for a long time!!! thank you
@MLEpath
Great overview! I love the point about projects, honestly , as someone who has been in the industry for 14 years I would go as far as saying that all best ML Engineers started with a personal project. When things get hard, you need the motivation of whatever attracted you to ML in the first place. For me it was photo organization (this is before Google Photos was available). Fingers on the keyboard is the best way to learn. Also, I'd say in 2025 PyTorch matters a lot more than Jax or Tensorflow
@deedee53852
Thank you for this video. You’re doing it right. What people need is not someone to say, "oh you can do it, there’s a lot of materials out there." Rather someone to guide them in filtering what's helpful at different stages. Again, thanks a lot for showing the empathy that people need in learning these things. Now I will write a blog about what I learned from this video.
@kartikagrawal8422
I was doing a math course for ML on coursera by Deeep Learning and i thought that i am wasting time. Thank you so much for motivating me.
@iamericlentz
Excellent advice, but giving up on a project is not "the worst thing." As a software developer, I have given up on a lot of projects, but learned a ton in the process. Sometimes you're just not ready, and you need to fill in some gaps and later that project you gave up on will seem like a cakewalk.
@thelmaotiono3999
I liked your video, most machine learning roadmaps or guides to learn Machine learning are really overwhelming for me but yours madw me feel like i can do it
@doomed5206
I think I am good at math ( integrals, derivatives, medium probability and metrices) have studied python basics. Can't wait to start on this journey in a few months. Will be religiously following you from now on.
@madeinhvn
Merry Christmas and Happy New Years Boris. This video is amazing. I am an embedded software engineer and I have decided to make a switch to ai. The "How Machines Learn" is a really amazing recommendation for us beginners. Thank you so much for this video!!
@ttt_7844
I truly enjoyed your approach and atmosphere. They embody an honest simplicity combined with precision, making it highly helpful. Thank you so much!
@ramazanAb
13:34 Would be great if you made video about reimplementing a paper
@banisan2035
Just in case you are German and want to learn the maths basics, I can also recommend Teschl's two "Mathematik für Informatiker" books. I used them extensively during my comp sci studies and decided to not listen to the lectures but instead just work through the books.
@Billwzw
Thanks!
@olavictor6286
Pls can you also do a roadmap on how to get an internship or junior role
@RomalHalimi-b6w
thanks Boris; I am from Afghanistan and actually my English language is not so good but your explain is so clear and I can know all of them.😍❤
@pedrolins5958
I really like your channel boris, thanks for this content. You’re awesome!!!
@borismeinardus