First Commit of Machine Learning
Hey everyone! This side Lucky Jha, a final year engineering student, so like everyone does I also started writing blogs for some reason and almost eve…
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From Learning Machine Learning to Competing on Kaggle: My First End-to-End Playground Competition Journey
How I applied Exploratory Data Analysis, Feature Engineering, Pipelines, and Ensemble Models to solve a real-world machine learning problem—and the le…
The Evolution of AI, Explained in Stages
AI feels like it "suddenly" got smart in the last few years. It didn't. It's been evolving in distinct stages for over 70 years — each one building on…
What Does `unsqueeze` Do in PyTorch? (And Why Your Model Keeps Asking For It)
You passed a single image to your model and got ValueError: expected 4D input (got 3D input) . Someone on Stack Overflow said "just add .unsqueeze(0) …
Bayesian Neural Networks
Adapted from an appendix of my MS thesis. Bayesian Neural Network Deep neural networks (DNNs) are usually trained using a regularized maximum likeliho…
GNN vs. Trees: High-Speed Hybrid Architecture for XLA Runtime Prediction
GNN vs. Trees: High-Speed Hybrid Architecture for XLA Runtime Prediction Introduction A common trap in Machine Learning engineering is deploying over-…
One "+x" That Made 100-Layer Networks Trainable: ResNet Skip Connections
Deep networks have a cruel paradox. In theory, more layers should never hurt — the extra ones could just learn to pass their input through unchanged. …
How Transformer Decoders Generate Text — From Causal Masking to Decoding
A Transformer Decoder does not generate a sentence all at once. It predicts one token. Then it feeds that token back and predicts the next one. That s…
Anthropic’s Fable/Mythos shutdown is the first real model export-control shock
Anthropic’s Fable/Mythos shutdown is the first real model export-control shock The important AI story this week is not just that Anthropic launched bi…
I Built an "Amazon-Style" AI Review Summarizer for Any Dataset (NLP, Transformers, Streamlit)
Have you seen those new AI-generated review summaries on Amazon? They are incredibly useful for buyers, but there’s a catch: they are completely locke…
Loss Functions: MSE vs MAE vs Cross-Entropy, Visualized
Pick the wrong loss function and your model optimises the wrong thing — perfectly. The loss is the single number training tries to shrink, so it quiet…
Fine-Tuning Llama 3.2 3B on Medical QA: Week 4 - When Lower Loss Meant a Worse Model
What Happened This Week Week 3 produced a working fine-tuned model: one epoch, one dataset, a clear improvement over the base model. This week 4 was s…
Flash Attention: what it does and why it matters
Flash Attention: what it does and why it matters Your training job is paying for an A100 at $3/hour. The loss is going down, gradients are flowing, an…
How to Become a Data Scientist in 2026
How I got here On principle, you will never catch me parading myself as a some sort of expert data scientist. Technically, that's what I do in my day …
The Machine Learning Engineering Series
Part 1: From Scratch to Systems . This machine learning series will be a real ride. It’s an interactive journey where I’ll be sharing and raising lots…
VLA or IL? A Controlled Dataset for Testing Whether Finetuning Turns Your VLA into a Fancy Imitation Learner
Motivation Robot manipulation is the ability of a robot to interact with and manipulate objects in the physical world, such as grasping objects, movin…
The Math Behind Neural Networks — Explained Like Nobody Did for Me 🧨
How does a neural network actually learn to be less wrong? Not the hand-wavy version. The real one. The one with the derivative, the chain rule, and t…
AlphaEvolve: Google DeepMind's Gemini-Powered Evolutionary Coding Agent
Inside AlphaEvolve: How Neural Networks and Evolutionary Algorithms Are Self-Optimizing Software For several years, the role of Artificial Intelligenc…
Handling Non-Stationary Time Series: Building a Probabilistic Engine with XGBoost & Python
If you have ever tried to apply Machine Learning to financial time series, you know the heartbreak of the "perfect backtest." You build a model, train…
Chain-of-Thought and Beyond: How LLMs Actually Learn to Reason
"The ability to reason step-by-step is not just a feature. It might be the difference between a language model that sounds intelligent and one that ac…
XGBoost: When Gradient Boosting Meets Regularization
1. The Problem It Solves Imagine you’re a loan officer at a bank. You have thousands of past loan applications with features like income, credit score…
Stop Guessing Which Weights Your Neural Network Actually Learned: Deterministic Initialization That Tracks Every Change
The Problem Nobody Talks About You've spent hours training your neural network. The loss converged, metrics look good, and you're ready to deploy. But…
The Paper That Taught Neural Networks to Learn Backwards
Last week I read the 1958 Rosenblatt paper. The one that started everything. The Perceptron, the first learning machine, the idea that memory lives in…
Removing PER From Rainbow DQN Set a New Snake AI World Record
Greetings all! Quick context: this is part of an ongoing series where I'm building Rainbow DQN one component at a time on Snake and measuring what eac…
🔬 AI for Scientific Discovery in the Real World: What Gemma 4 Changes The Moment AI Leaves the Chat Window
This is a submission for the Gemma 4 Challenge: Write About Gemma 4 🔬 AI for Scientific Discovery in the Real World: What Gemma 4 Changes The Moment A…
Did My LoRA Learn Tenacious Style—or Just Memorize Augmented Patterns?
In Week 11 Tenacious-Bench, we trained a LoRA adapter on Tenacious-style B2B sales emails using Supervised Fine-Tuning (SFT). We got a real performanc…