jyotipmahes/ML-Interview-Prep
Resource
Can I trust it?
Be careful with this one.
Warnings Check
Very new: it was created yesterday. Wait a little before installing it.
Stars from real accounts No data
We haven't checked its stars for fakes yet.
Active OK
Last change today.
Licence Careful
No licence: legally you can't reuse the code, unless the README says otherwise.
Quick checks from public data. They help, but they are no guarantee.
What it is
A Jupyter notebook collection of from-scratch implementations of core machine learning algorithms, including linear and logistic regression, K-Means, KNN, a 2-layer MLP with manual backprop, layer normalization, multi-head self-attention, LoRA and byte-pair encoding, with math…
Who it's for
Machine learning engineers and candidates preparing for MLE coding interviews
How to use it
Ask your AI to set it up
Paste this into Claude, ChatGPT or your coding assistant.
Help me install and set up jyotipmahes/ML-Interview-Prep in my project. Follow its README: https://github.com/jyotipmahes/ML-Interview-Prep. Explain each step and check it is safe before running anything.
Star curve
On the radar
Its place among the radar's top 100, day by day, with #1 at the top. Gaps are days it was out of the top 100.
Records
- Best place on RepoAlerts: #92, on 1 Nov 2026
Get alerts for repos like this
We'll email you when repos like this start rising. Free, once a week, only what matches.
23,610 GitHub repos watched and ranked every hour. Figures as of 1 November 2026.
What arrives: one email on Mondays with the repos that match, never more. See last week's. Privacy
For maintainers
Add this badge to your README. It shows the repo's place on the radar, updates every hour and links back to this page.
[](https://repoalerts.com/repo/jyotipmahes/ML-Interview-Prep?ref=badge)Similar repos
- TrenTorch/TrenTorch
An educational repository with a from-scratch machine learning framework built on NumPy, plus a browser-based set of coding questions and a Python CLI curriculum covering tensors, autograd, training,
- Hongyang-Du/PaperLeet
An offline practice library for turning research papers into code. It offers 49 papers and 63 exercises covering attention, reinforcement learning, diffusion and flow, and related methods. Each exerci
- MUSE-AI-Lab/ReMCTS
Research code for ReMCTS, a Monte Carlo Tree Search method for LLM code generation. Each candidate program is executed in a subprocess, failures are stored as structured reflections in path and global
- YeonwooSung/llm-architecture-from-scratch
A collection of from-scratch PyTorch implementations of modern LLM architectures, including GPT-2 XL, Llama variants, DeepSeek V3, Qwen3, and Gemma 3. A comparison table lists each model's normalizati
- qlabs-eng/noise
A pretraining speedrun for learning algorithms that never run a backward pass. It fixes the 37.7M-parameter Dust transformer, a 30M-token FineWeb training set and a validation cross-entropy score, and
- NVlabs/ASPIRE
A research framework for robotics in which an LLM-driven coding agent refines sensorimotor skills through iterative debugging and evolutionary search instead of gradient-based training. Evaluated on L