A Comprehensive Guide to MRI Analysis through Deep Learning models in PyTorch Photo by Olga Rai on Adobe Stock.First of all, I’d like to introduce myself. My name is Carla Pitarch, and I am a PhD candidate in AI. My research centers on developing an automated brain tumor grade classification system by extracting information from…

It’s been no more than a year now, where GPT stardust ✨ covered almost any sector globally. More and more experts, from any field, crave to utilise Large Language Models (LLM) in order to optimise their workflow. Evidently, the corporate world could not be absent from this new trend’s safari. The future promises unprecedented possibilities,…

The need for insights LLMs like ChatGPT, Claude 2, Gemini, and Mistral captivate the world with their articulateness and erudition. Yet these large language models remain black boxes, concealing the intricate machinery powering their responses. Their prowess at generating human-quality text outstrips our prowess at understanding how their machine minds function. But as artificial intelligence…

From the OmniXAI, Shapash, and Dalex interpretability packages to the Boruta, Relief, and Random Forest feature selection algorithms Image created by the author at DALL-E“We are our choices.” —Jean-Paul Sartre We live in the era of artificial intelligence, mostly because of the incredible advancement of Large Language Models (LLMs). As important as it is…

A deep dive into Stable Diffusion and its inpainting variant for interior design In this fast-paced world that we live in and after the pandemic, many of us realised that having a pleasant environment like home to escape from reality is priceless and a goal to be pursued. Whether you are looking for a Scandinavian,…

How changing my perspective on layoffs actually set me free 12 min read · 19 hours ago Look at you oh you handsome captain steering the wheels of your life — Image by Author (Dalle)Imagine finally landing your dream job after years of hard work. You’re at the top of the world,…

An in-depth exploration of histograms and KDE A histogram is a graph that visualizes the frequency of numerical data. It is commonly used in data science and statistics to have a raw estimate of the distribution of a dataset. Kernel density estimation (KDE) is a method for estimating the probability density function (PDF) of a…

In the trade flow maps, I aimed to represent two-way trade relationships between countries. For example, the export from Nepal to India would be represented by the first arrow (A1-A2) and the import by Nepal from India would be represented by a second arrow (A3-A4). In this way, each country pair relationship would require four…

State-of-the-art data platform design 12 min read · 13 hours ago Photo by Nubelson Fernandes on UnsplashIn this story, I will try to shed some light on the benefits of modern data warehouse solutions (DWH) compared to other data platform architecture types. I would dare to say that DWH is the most…

Using batting stats from Major League Baseball’s 2023 season Shohei Ohtani, photo by Erik Drost on Flikr, CC BY 2.0Outlier detection is an unsupervised machine learning task to identify anomalies (unusual observations) within a given data set. This task is helpful in many real-world cases where our available dataset is already “contaminated” by anomalies. Scikit-learn…