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I see some people started programming in 6th,7th standard Meanwhile, I got a laptop at 21 How to keep up with these guys Sometimes it creates too much inferiority complex getting early exposure to the internet and laptop can benefit a lot

Getting access to pc or a laptop at an early age is a privilege in India You cannot change my mind It gives so much edge if you use it in the right way

Average ML engineer after grinding for 10 years

I was just reading a blog on linear algebra by 3blue1brown while sitting in metro The person next to me noticed it and asked about these things He is working in AMD with 14 years of experience in the machine learning space as the conversation continued he suggested to me to go deep into NLP and LLM'S

If anyone tells why you should study maths before ML is because of this Every algorithm is just a wrapper of some mathematical topic

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No hate to her, this is the reality of the Indian corporate system My friend, who did not even know how git works, got 12lpa job in one of the Big 4 Before anyone attacks me, he still has not cleared his M3, which we took 4 years ago His father's brother is in the top position of the company, and through their influence, he is working without a degree certificate

The only playlist you need to start with MLOPs smooth like butter

Math and ML → Part 1: The Mathematical Foundation of Regularization Regularization is one of the most crucial techniques in machine learning for preventing overfitting. But have you ever wondered why it actually works from a mathematical perspective? The Problem: When a model overfits, it essentially memorizes the training data instead of learning the underlying patterns. This leads to excellent performance on training data but poor generalization to unseen test data. The Mathematical Root Cause: Let's dive into the math In ordinary linear regression (first equation), we estimate parameters (θ*) by solving a system of equations. Here's where things get tricky: When your feature matrix exhibits high multicollinearity (features are highly correlated), certain columns become linearly dependent on others. Mathematically, this drives the determinant of the matrix toward zero, making it singular or leaning more towards a singular matrix. The problems? The inverse becomes unstable, leading to: >Unreliable parameter estimates >Extreme coefficient values >Poor model generalization And here's the reality: Multicollinearity isn't some edge case; it's incredibly common in real world datasets. The Mathematical Solution: Regularization, look at the second equation. Notice how the regularization parameter (α) is added to the diagonal of the matrix? By adding αI to X^T X, we're mathematically guaranteeing that the matrix remains invertible, regardless of multicollinearity in the original data. Even when X^T X is singular, (X^T X + αI) is always invertible for α > 0. This ensures: >Stable parameter estimation >Controlled coefficient magnitudes >Better generalization to new data This is Part 1 of my "Math & ML" series, where I'll bridge the gap between mathematical theory and practical machine learning. I want to show you the "why" behind the algorithms, not just the "how." If you found this insightful and want more content connecting mathematics to ML intuition, let me know in the comments! Retweets appreciated to help others discover the mathematical beauty in ML!

Covering math before starting ML increases your iq and capability to understand algorithms by 500%

Some good reddit communities r/aiagents r/researchML r/openai r/languagetechnology r/neuralnetworks r/learnmachinelearning

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No luck only work Good morning

A lot of people were asking me for math and ML-related resources First of all, I am not a pro, i am still learning, and there are a lot of free resources to learn from YouTube and many other websites. I will share what I have referred to and what I will refer to in the future. If I get any doubts, Go through this thread

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Perfect

I see some people started programming in 6th,7th standard Meanwhile, I got a laptop at 21 How to keep up with these guys Sometimes it creates too much inferiority complex getting early exposure to the internet and laptop can benefit a lot

Is this normal 😭 Any suggestions for dandruff plz

Average ML engineer after grinding for 10 years

Legand

🧿 nazar is real guyz

Today i sent my resignation mail and officially my notice period begins Really i am very much thankful to this job and opportunities especially money even though it is less but for me it was good enough to survive in Bengaluru Honestly when I look back on my life the only constant thing is going up Many people start with a decent life but I started from the negative I have seen everything in these 22 years of life Currently I have savings for the next 6-8 months and no job offers and I'm not trying for a job also My only goal is to get a good rank and good college for post-graduation Even if i fail it doesn't matter bcz still I will be in a good position to do something compared to these 22 years i will put my efforts irrespective of the results 179 days left let's go

I will meet you guys after 4 months Don't be scared if i become the ceo of openai I'm coming sama

NLP or deep learning? After classical ML

Am i the only 22 year old virgin here?

lore: >Don't be me comes from a family where my sister and I were the first ones to go into engineering colleges Studying was the only option I had, and the only guide I had was my sister Did schooling from a government school, which is closed now due to building collapse and bad infrastructure First one to graduate with a computer-related degree, and the second one to do it in engineering Did not even attempt JEE, but did well in KCET, got a good ranking, and I had the opportunity to join good colleges in BLR did not join due to money issues, but got a government seat in my own district as I had a decent rank and low income dumb ass me did not know jack shit about computers, still joined AIML because it was the future, when everyone was learning programming, I was learning English First 3 sems covid fked it, the only thing I learned properly was maths and got a good theoretical knowledge No programming experience apart from college labs. Started learning about programming in the 6th sem and got my first laptop in the 7th sem cleared TCS nqt and joined(i know its not an extraordinary achievement but that was the first tech job anyone had in my entire my family) realised I can do more and better after coming to Bengaluru And I am trying my best to do I know it's not a great story, but for me it is One small mistake could have turned my life into much worse cuz the environment and friends I had were into different kinds of things from childhood, but still chose not to indulge in those kinds of activities I may be late, but I will never go without doing the things I want to Thanks for reading peace.

Getting access to pc or a laptop at an early age is a privilege in India You cannot change my mind It gives so much edge if you use it in the right way

Small upgrade The kid inside me is very happy 2 years back - no laptop 1 year back - just a laptop Today - mini setup Hopefully I can add new things in 2026

Dream job -> ML engineer at OnlyFans Models train i watch

Life as a 22-year-old married male is really difficult While your friends are chilling, you are here working hard

peak male happiness This is all you need to become a software engineer in 2025 How did they do it without Claude and gpt dsa vs dev etc etc