K-Means Clustering — What Every Data Scientist Should Know
Author(s): Aamir Raja Originally published on Towards AI. Discussing and simplifying intricacies of K-means clustering for machine learning. Photo by Igor Omilaev on Unsplash K-means clustering. What exactly is this? It’s an extremely useful machine learning model that creates clusters in order …
No Libraries, No Shortcuts: LLM from Scratch with PyTorch
Author(s): Ashish Abraham Originally published on Towards AI. The no BS guide to build, train, and fine-tune a Transformer architecture from scratch OpenAI has recently launched its highly anticipated open-source GPT-OSS models, a moment that invites a minute of reflection on just …
Universal Deep Research: Beyond Search Engines
Author(s): Piyoosh Rai Originally published on Towards AI. The fundamental difference: Search engines retrieve documents linearly, while deep research systems orchestrate specialized agents across multiple sources, synthesizing evidence and validating findings through interconnected intelligence networks. Why your AI research assistant is just …
Multilingual Text Detection with FastText and Hugging Face: A Beginner’s Guide (Part 1)
Author(s): Gift Ojeabulu Originally published on Towards AI. Image by author Introduction Language detection is one of the first and most crucial steps in any multilingual Natural Language Processing (NLP) pipeline. Before you can translate text, classify it, or feed it into …
Why Does Hypothesis Testing Matter in Machine Learning?
Author(s): Nikhil Dasari Originally published on Towards AI. Understanding the Role of Hypothesis Testing in Machine Learning. When I first started learning Machine Learning, I was confused about how hypothesis testing is used. Many of you may have had this same doubt …
Small Language Models Are the Future of Agentic AI: Here’s Why
Author(s): MKWriteshere Originally published on Towards AI. Why specialized SLMs under 10B parameters are replacing 175B LLMs in production AI agents — with 30x cost savings, better performance, and a proven migration roadmap. If you’re running AI agents in production, you’re probably …
Claude Sonnet 4.5: The AI That Builds Software as You Speak
Author(s): Gaurav Shrivastav Originally published on Towards AI. From fixing real-world code to imagining apps on the fly, Sonnet 4.5 turns software creation into a live collaboration. What if you could build software differently? Image Generated by Gemini Nano BananaAnthropic’s release of …
Transfer Learning in AI: Reusing Knowledge to Solve New Problems
Author(s): Aditya Gupta Originally published on Towards AI. Introduction What would be easier: teaching someone to play the guitar who has already learned the piano, or teaching someone who has never touched a musical instrument? Most of us would agree that the …
Automating Data CI/CD for Scalable MLOps Pipelines
Author(s): Kuriko Iwai Originally published on Towards AI. A step-by-step guide to achieving continuous data integration and delivery in production ML systems Building robust Machine Learning (ML) applications demands meticulous version control for all components: code, models, and the data that powers …
How Soft Tokens Are Making AI Models 94% More Diverse at Reasoning
Author(s): MKWriteshere Originally published on Towards AI. Meta’s breakthrough lets language models think in continuous concepts instead of discrete words with zero computational overhead Current AI models think by choosing words. One word at a time. Like you’re navigating a maze by …
Building Python Automation Systems That Saved Me Months of Work
Author(s): Code with Margaret Originally published on Towards AI. How I streamlined data, reports, and workflows into efficient pipelines When I first started automating with Python, I underestimated just how much time I could save. At first, it was small scripts — …
Beyond ML Loss Function: Cost Functions and Hypothesis Testing in Supply Chain
Author(s): Siddharth Mahato Originally published on Towards AI. Understand how Cost Functions and Statistics can help you go beyond accuracy with visuals and examples. Source: Image on Unsplash Manufacturing is a large and crucial part of the economy. It involves processing and …
Do AI Agents Really Use the Tools You Build for Them? I Tested It.
Author(s): Marie Humbert-Droz, PhD Originally published on Towards AI. Testing tool coverage in local agents and how to improve compliance. I thought my healthcare AI agent would call my lab-checking tool every time it encountered lab values. Instead? Only 1 out of …
Understanding Neural Networks — and Building One!
Author(s): Aditya Gupta Originally published on Towards AI. Why Do We Need Neural Networks? Imagine trying to teach a computer to do something humans find easy like recognizing a face in a photo, understanding someone’s accent, or predicting which movie you’ll enjoy …
In-Context Learning Explained: Why LLMs Need 100 Examples, Not 5
Author(s): MKWriteshere Originally published on Towards AI. New research reveals the truth about few-shot learning and what it means for your AI applications What happens when you feed ChatGPT examples in your prompts isn’t what you think Image Generated by Author Using …
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