Part one answered "what is attention - How they let a model focus on what matters in a sequence rather than treating everything equally. This post answers a harder question: Does it actually work? I pulled attention mechanisms out of their comfort zone (text, language models, translation tasks) and dropped them into something messier: raw brain signals. The question was simple. Do these techniques actually hold up when the data isn't words in a sentence — but electrical acti

Here's what actually sparked my interest in Attention Mechanisms Back in 2021, I was working on a research study - "EEG Emotion recognition using DEAP dataset" EEG (Electroencephalogram) - if you haven't heard of it, is basically a way to record electrical activity in your brain ,you wear a headset with electrodes, and it captures your brainwaves in real time. The DEAP dataset is a collection of EEG recordings from 32 participants who watched music videos, with their emotio

I. The Goal: Testing the Hype In my last post, I documented how I built a custom dataset by pulling live data directly from Wikipedia. It was a process of turning messy web tables into a structured CSV file. Today, I’m putting that data to work to answer a question many of us have: Are record-breaking box office numbers a consistent new trend or are we just seeing a few lucky hits? By looking at the last 30 years of cinema, I wanted to see if the "Billion Dollar Club" is actu

Introduction: Challenging the Traditional Analytics Workflow Usually, the roadmap for building a data portfolio follows a very specific, linear path. The formula is familiar to almost everyone entering the field: Find a pre-cleaned dataset on a portal like Kaggle. Download the static CSV file. Clean any minor remaining errors using Excel, SQL or Power BI. Visualize the results in a standard dashboard. It’s a safe and effective process for learning the basics. However, as

Decoding the Silent Language: How Visuals Turn Bio-Data into Action Your body is constantly speaking to you, but it speaks in a language of numbers that most of us can’t instinctively understand. Every heartbeat and sleep cycle is a data point in the vast experiment of the "Quantified Self". As a Data Analyst, I believe our job is to act as translators. If we use the wrong visual "lens," the story of our health becomes noise. But with the right representation, we can finally

My journey through Sprint-1: turning medical data into insights that could save lives. What is Sepsis? Sepsis is the body’s extreme...

A blog intended for newbies and those who thrive to produce better insight with the help of Calculated Fields. Calculated Field as the...

Structured Query Language or SQL One of the most popular and easy-to-learn tools for data analysis is SQL. It let us retrieve , filter ,...

Do you want to know the crucial biomarker for liver health?