Forward Propagation Explained: The First Step to Training Neural Networks
In order to understand how to train an LLM, we first need to understand backpropagation. And before we get there, we need to understand the stage where everything begins: forward propagation.
Inside the Mind of a Perceptron: Watch It Learn!
If you are like me who just wanted to learn about LLMs without learning about the simplest unit of neural networks, the perceptron, then this article is for you!
The Math I Need for Transformers
Before diving deep into LLMs, I wanted to get comfortable with the math behind them so the theory actually makes sense. So, I started exploring the building blocks - dot products, softmax functions, cross-entropy loss, and backpropagation through attention...
"I Sus?" Understanding Isolation Forest and Local Outlier Factor
These days, we rely heavily on Large Language Models (LLMs) for almost everything — from making predictions, finding anomalies, to even helping out with EDA. Let's be honest, we've all done it...
Divide and Cluster: The Art of K-Means
So far, we've explored some powerful algorithms like Regression, SVM (Support Vector Machines), and Naive Bayes — all designed to work with labeled datasets, where each data point comes with a tag, a class, or a target value...
From Structured Predictions to Smarter Decision-Making with Decision Tree
Decision trees give us a systematic, logical approach to prediction and classification in the machine learning universe. They mimic human decision-making by breaking down problems into smaller steps...
The Terror of Bayes' Theorem
Class 6th (as far as I can recollect) is when we are introduced to probability. Not gonna lie it used to be my favorite topic to study until Mr. Reverend Thomas Bayes was introduced and his theorem. I could never wrap my head around it...
SVM in 2025: Old School or Still Cool?
Support Vector Machines (SVM) were once the go-to algorithm for classification tasks, offering high accuracy and robustness in structured data...
Is Your Model Cramming Too Hard?
Finishing off our regression series, we bring to you the last article on it, covering Ridge and Lasso Regression.
Honey, I Shrunk the Dataset!
So, I was working on this dataset with 1.2 million rows — sounds massive, right? Well, guess what? That's just the tip of the data iceberg. Fun fact: this is only considered medium-sized data...
All the Statistics You Need to Know for Linear Regression
Imagine you're trying to figure out how much candy you can collect depending on how many houses you visit on Halloween. You want to draw a line that shows how your candy collection grows as you visit more houses...
The Good Girl's Guide to EDA
If you're like me and greet a new dataset the way my dog reacts to a vacuum cleaner — paralysed by confusion, betrayal, and a touch of existential dread— this guide is for you...