@ClairSignal

I think a good methodology to do independent research in ML/AI without getting yourself into a tutorial loop is to constantly verify conclusive statements from all the external resources out there at some practical level. By verifying those concepts with experiments, you not only stand on a more solid factual ground, but also gained experience in implementing experiments, which is much more valuable and arguably the most important skill in the field of ML/AI research. I dropped a video reacting to Jeffery's learning process and give my own two cents on this methodology/heuristics for AI research here: https://youtu.be/5FM_0RUJhYo?si=XC-l45D6A-NlKglg. Feel free to check it out and leave your opinion!

@maxheadrom3088

The best teacher I had in Engineering School used to say at the end of every class: "Did you learn it?" and everybody would say "Yes!" and he would say "You didn't! You understood it! Now go home and do these problems because that's how you learn!".

@minervali631

The point about math is probably backwards. Doing math is not about solving some differential equations. It's about gaining understanding and intuition. Some level of exercises is needed, but unless you are solving those problems on a regular basis, you are going to forget anyway. Intuition and understanding probably is going to stick for longer.

@cnydo

The hard truth about math is that you still have to learn it the text book way. Visualization videos are nice but at the end they only touch a small corner of each topic

@federicoaschieri

Mathematics is learned by solving thousands of problems. Learning only the theory is like learning the rules of basketball, watching the others play, and think you can play as well.

@Blackwhite2277

Recap: shoot for a balance between learning and doing/coding to produce tangible projects

@sandd5241

this was a wonderful video. i don’t feel like this type of honesty is very common on youtube

@makesushi

i am not even joking when i tell you this, i made an entire schedule to study like 60% of these topics by the end of this year (ml, math dsa (theory focus)), instead of data engineering i was going to deep dive haven't watched the video but wow the yt algorithm is good.

edit: i hope each one of you reading this achieves your learning goals this year ! lets change the world

@ravikiran0092

That is solid advice. Learn the basics. Then build projects to connect the dots. In this process, expand your knowledge.

@anantshukla3415

I am a uni student currently studying deep learning and computer networks, whenever I stumble upon a math concept that I am not familiar with I actually like to get lost in the rabit hole and explore more, but I kinda get your point, juggling all of this with a job and a family must take a lot of effort, on the contrary it is great that you were able to learn all of this within a year.

@고양이집사-o3k

Completely Agree. I too, spent a lot of time building math fundamentals by studying alone. But looking back, theres really nothing to put on my resume, and I cant really market myself to prospective employers. As a recent grad, this is a non trivial issue. The resolution I came up with is to make this year the year of project-based learning. Cheers!

@Hand-x1j

I had a similar experience starting from 2017 to 2022—even if you did not achieve everything, you still built a base for your next try. Now I can easily study the content of 5 years in just one year, and I work in a similar career, which is heavily technical. 

You just have to keep trying and modifying your strategy until you reach a certain mental state where acquiring skills is like a flow. it took me three years of trying and failing until i improved my methods 

There is also a very important aspect: knowledge, especially multidisciplinary knowledge, will converge at some point and will explain itself.

@LewyM7

i am a final year CS student and this really resonated with me, i really want to get into computer vision and am working on a study plan and this reminded me that project based learning needs to be 80% of the work

@ZiYawChee

This is what I have been experiencing lately, stuck in this infinite learning loop. I gonna start with hands-on project and go in-depth from there. Thanks for your sharing!

@andyw732

Great reflection on how it’s easy to fall into a rabbit hole when learning new topics. Appreciate your self honesty when it comes to learning without practice you’ll probably forget: but I do believe it’s sometimes necessary to build a base.

@isweartogod

9:32 — I know you meant to say there wasn’t anything you produced, but I would argue what you did still stands as an accomplishment. You should be proud of balancing a job, your family, and making time to learn all this cool stuff — sounds to me you did accomplish something just perhaps not in the most optimised manner. Thank you for sharing!

@ChandlerRandolph-d6b

the self-reflection and key takeaways at the end are on point. Throughout my learning journey my biggest flaw was not using the concepts that I learned and not solving to a problem. Solving to a problem meaning asking myself what the problem is I'm trying to solve? instead of solely focusing on the tools. It's good to have a broad knowledge of different tech stacks and methodologies but at the end of the day it comes down to the problem at hand and why it's important. Asking Why and clearly articulating the fundamental problem at hand is the bedrock to retention as it's important to the problem.

@levelup2014

Ahh the old Theory Vs Practice dilemma,  we all know this intuitively but we still cling to the "One more video, One more course, One more book" idea.

There has to be a deeper reason why our brains think like this when we know tangible practice is the correct answer 80% of the time

@codeapprentice5123

I also studied a lot of deep learning this year and the only stuff I remember really is the stuff I built projects with. I learnt about CNN's, RNN's transformers, reinforcement learning, recommendation algos. I ended only building projects using CNN's and RNN's (mostly due to data availability and compute). I can tell you a lot about how CNN's and RNN's work and good network architecture depending on what problem you optimising for but nothing about other network architectures.

@tanishksinha849

Great video jeffrey, I too had a similar realisation some days ago, when I participated in my first hackathon. Even though it was all here and there, I learnt a lot more in those hours than I could in weeks