ML Was Hard Until I Learned These 5 Secrets!

Learning machine learning is really hard, but during my 3.5 years of studying ML, I learned 5 secrets that made understanding ML much easier and helped me a lot in "mastering" it!
In this video, I will share these 5 secrets with you, so that you don't have to spend years figuring them out yourself.
Enjoy 💛

⬇️ Follow me on my other socials and feel free to DM questions! ⬇️

================== Timestamps ================
00:00 - Intro
00:29 - The Secret to Math 1
03:32 - The Secret to Math 2
05:36 - The Secret to Coding
07:53 - The Secret to Understanding Code
10:13 - The Secret to Mastering ML
=============================================

#ai #datascience #machinelearning

[hussainshaik]

I gave up learning deep learning many times. Then in 2021 i had painful divorce. It changed everything instead of going into the depression i channeled my energy into learning deep learning. Now i am able to train small llms and text to speech models from scratch on multiple gpus. I am starting a company in the next month!

[rma]

I took Deep Learning and Machine Learning subjects at the university last semester and now in the current semester. The Deep Learning professor would explain the theoretical process in plain English with graphical representations before even showing any math formulas. By that time, I get quite comfortable with what I'm learning or about to learn since I know the process and the end goal. The only thing I look for in the formulas is certain details or how exactly what is happening in each step if I'm too curious. On the other hand, my Machine Learning professor, if I attend the class, all I hear is math. When I go home, all I have to study from is the slides, which are again all math with no explanation in plain English. I ended up dropping the subject. It's crazy how a teacher can make someone love/hate a subject or make them feel good/bad at the subject

[youjean]

The day I stopped hammering formulas into my head, I understood how amazing math actually is! My advice to my younger self would be to try to understand the intentions behind all those formulas and not to force it. Occasionally, you discover why you need it when you need it.

[kingoftennis]

He forgot rule 1: talent for sitting and focusing for days without getting up for food or daylight

[Sendero-ypgi]

Thanks for this (and also for the other videos) man! You can really see you're down to earth and you'va faced the same struggles everyone has in the journey towards becoming better ML scientists/practitioners!

[carpediemcotidiem]

00:01 Understanding math the right way is crucial for learning machine learning.
01:39 Translate human ideas into math concepts
03:18 Understanding math derivation rules simplifies ML learning
05:02 Recognize patterns and practice is key to mastering ML.
06:40 Realizing that debugging is coding helps with implementation
08:18 Understanding large code bases with a simple strategy
09:56 Setting breakpoints in the main function for debugging is crucial in understanding ML implementations
11:41 Mastering ML takes time and dedication.
Crafted by Merlin AI.

[mioox]

This video is a breath of fresh air. I was frustrated because I couldn't understand how to use einops for 3 hours and I was only writing 1 line, I'm glad I stumbled upon this

[frostbarrier]

I just started few weeks ago, I felt very lost, but I am still learning and reading things, thank you so much for this amazing video my friend!

[rranga]

Thanks for my birthday present. It’s nice to know that still there are people who believe in a system. Much appreciated.

[Neuralbench]

Its like you have opened a new window for me into ML world. I was stuck at figuring out which topic falls into which category, but after listening to you it all came together. Now i can organize my thoughts properly while thinking and learning. I can relax while reading math formulas and be content by just understanding the intent behind it. I can relax while going through derivations knowing that it is pure mathematical realm and i can tackle it separately. And finally now i am slowly beginning to understand how to break down my tasks and work aka apply first principles thinking to ML problems. In short, you have helped me form a initial mental schema for ML. Thanks a lot !

[davethinkingsystems]

really really good. I think you have explained this very well. I think I knew a lot of this from my own experiences of learning different things over my life but you explained this well and I found your words truly encouraging. Thanks.

[puligaddan]

Very nice explanation by breaking things down and addressing the right points. This is very helpful and encouraging. thank you for this video.

[ellenc]

Thanks for keeping it real! :) I have a renewed perspective and I think I'll be able to enjoy the process more!

[SamanyuGupta-lhwg]

Thanks! this video has really saved me from the upcoming traps and forged a path through.

[MrJeeoSoft]

Awesome!!! I loved your Math explanation! Thank you very much!

[mayankumar]

Boris i really like u and connect with ur style. U simply state ur experience and how u r improving and i somehow keep that as a benchmark and learn from that

[kirtisardana]

So relatable ...I just relived all the moments you mentioned in detail ... Though I had given up on ML ....will start again now ❤

[MalamIbnMalam]

The thing that gets me about Deep Learning are RNNs, then going through LSTMs and GRUs. I try to memorize what happens throughout the entire RNN with activation layers and backwards propagation through time. It is just a lot of over-convoluted complex stuff. I just started learning Machine Learning and Deep Learning in August of 2023.

I am just struggling so much with it, but I love it. I love watching lectures on Transformer sequences with encoder and decoder even though at first a lot of it sounds like Ancient Greek to me. I will keep trying

[davidcoleman]

Thank you so much for this Boris as has helped me so much as I am learning ML

[qaviahmedurrehman]

great job mate really I hope they teach us this stuff at the uni. Keep it man