Ramsha Khan @geekyramsha
Curious mind into ML/DL | Mathematics | Exploring RL khan-ramsha.github.io Mumbai, Maharashtra Joined December 2023-
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Another example hit me with a reminder - "escape the comfortable path to find growth" PS: the figure below is all about the good updates happens when on steeper surfaces rather than on gentle ones.
Implemented KMeans (unsupervised) and Decision Tree (supervised – core idea) from scratch. 🔗github.com/Khan-Ramsha/ML…
Pal pal jeena muhal mera tere bina, Ye saare nashe bekaar teri aankho ke siwa ....
Isn't human memory so selective? I can remember the exact words my school teacher said at specific time in a specific classroom. I can remember a girl's compliment about my eyes in the lab with precise detail xD Yet can't remember a schoolmate even after she tries to remind me.
This is crazy!! A Lean 4 proof from Harmonic's Aristotle (AI system) achieved Gold Medal-level at the IMO, printed on dot-matrix paper. Retro hardware meets cutting-edge AI math!
This is crazy!! A Lean 4 proof from Harmonic's Aristotle (AI system) achieved Gold Medal-level at the IMO, printed on dot-matrix paper. Retro hardware meets cutting-edge AI math!
Was revisiting cost functions for logistic regression and this statement made me think twice. Isn't this incorrect? In Logistic regression, binary output follows Bernoulli Distribution. Gaussian is used for linear regression and that's for noise/error term -> y = θ ^ T * x + e.
Calculus - where respect is optional 😄
Calculus - where respect is optional 😄
@fareedsayed95 By reverse engineering I meant - starting with the high level stuffs (the big picture) then working backwards into deeper details when surface level explanation doesn't fully satisfy you. That's "top-down approach".
So reverse engineering has always made sense to me. Brushing up math and ML foundations (and since I can't digest theory for long, I'll implement concepts I can experiment with) Implemented perceptron learning rule from scratch (kinda like an optimizer) github.com/Khan-Ramsha/ML…
My instagram is full of people grooving to "kache ashona aroo kache ashona". No clue what it means but there's some vibe in the song 💃🏻
Quick update: Earlier shared multi-head attention with kv cache then later while working on decoder architecture, removed kv caching for now due to complexity. Now it's back again (in a separate file). 🔗github.com/Khan-Ramsha/Fi…
Quick update: Earlier shared multi-head attention with kv cache then later while working on decoder architecture, removed kv caching for now due to complexity. Now it's back again (in a separate file). 🔗github.com/Khan-Ramsha/Fi…
hot take: if you want to learn ML foundations, skip the tutorials. watch recorded lectures from top uni professors instead.
Isn't debugging by writing print statements the most underrated (and simplest) way to catch mistakes!
Ran into some tricky "tensor dimension errors" while running training loops on my custom Qwen2 arch. Got pretty deep into how pytorch manipulates tensors to make it work! jotted down everything in my head after this. Check it out :- notion.so/How-transpose-…
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