How Do AI Content Detectors Work?
AI content is everywhere. ChatGPT’s explosion in popularity has created a surge in AI-generated blogs, articles, emails, resumes, and academic papers. Naturally, AI content detectors have grown in response. Many schools and publications have used AI-driven plagiarism checkers for years. Now that it’s easier for people... Read more
AI-Powered Natural Language Queries for Knowledge Discovery
In this article, I wanted to share a proof of concept project I’ve been working on called UE5_documentalist. It’s an exciting project that uses Natural Language Processing (NLP) to potentially enhance your experience with massive documentation. While I worked on the Unreal Engine 5 documentation for... Read more
The Importance of Implementing Explainable AI in Healthcare
Healthcare systems are implementing AI, and patients and clinicians want to know how it works in detail. Explainable AI might be the solution everyone needs to develop a healthier, more trusting relationship with technology while expediting essential medical care in a highly demanding world. What Is... Read more
Top 10 Pre-Trained Models for Image Embedding Every Data Scientist Should Know
The rapid developments in Computer Vision — image classification use cases have been further accelerated by the advent of transfer learning. It takes a lot of computational resources and time to train a computer vision neural network model on a large dataset of images. Luckily, this... Read more
Organizational Processes for Machine Learning Risk Management
In our ongoing series on Machine Learning Risk Management, we’ve embarked on a journey to unravel the critical elements that ensure the trustworthiness of Machine Learning (ML) systems. In our first installment, we delved into “Cultural Competencies for Machine Learning Risk Management,” exploring the human dimensions... Read more
RAG vs Finetuning — Which is the Best Tool to Boost Your LLM Application?
As the wave of interest in Large Language Models (LLMs) surges, many developers and organisations are busy building applications harnessing their power. However, when the pre-trained LLMs out of the box don’t perform as expected or hoped, the question on how to improve the performance of... Read more
Conditional Probability and Bayes’ Theorem Simply Explained
Conditional probability and Bayes’ theorem are fundamental ideas in statistics that even laymen have heard of. Bayes’ theorem also gives rise to a separate branch of statistics, namely Bayesian inference. In Data Science we mainly deal and work in a Frequentist world and so we are, in my opinion,... Read more
Evaluating Clustering in Machine Learning
Clustering has always been one of those topics that garnered my attention. Especially when I was first getting into the whole sphere of machine learning, unsupervised clustering always carried an allure with it for me. To put it simply, clustering is rather like the unsung knight... Read more
Python Timestamp: Converting and Formatting Essentials for Beginners
Do you know what’s the number one thing Junior and Senior Developers have in common? They both don’t know how to work with dates without referencing the manual. It’s just one thing that’s too difficult to remember for some reason. Well, not anymore! Python Timestamp plays... Read more
Data Engineering vs Machine Learning Pipelines
Data engineering and machine learning pipelines are both very different but oddly can feel very similar. Many ML engineers I have talked to in the past rely on tools like Airflow to deploy their batch models. So I wanted to discuss the difference between data engineering... Read more