Tired of abstract theory? This tutorial shows you how to implement vector search without relying on external libraries.

Making developers awesome at machine learning
Making developers awesome at machine learning
Tired of abstract theory? This tutorial shows you how to implement vector search without relying on external libraries.
A concise and approachable explanation of loss functions for beginners.
Learn how to turn your machine learning model into a safe and scalable API using FastAPI and Docker.
Why label thousands of data points when your model can tell you exactly which ones it needs?
Learning advanced concepts of LLMs includes a structured, stepwise approach that includes concepts, models, training, and optimization as well as deployment and advanced retrieval methods. This roadmap presents a step-by-step method to gain expertise in LLMs.
Machine learning (ML) is now a part of our daily lives, from the voice assistants on our mobiles to advanced robots performing tasks similar to humans. It has transformed many sectors like healthcare with tools to assist doctors in diagnosing diseases, the automobile industry by introducing self-driving cars, retail by enhancing customer experiences through personalized […]
I believe in the ‘learning by doing’ approach—you learn more this way. However, as a beginner, you need to be careful not to overwhelm yourself by jumping into a complex project too soon. To help you get comfortable working with LLMs and RAG, I’ll be sharing 5 different projects that are perfect for beginners. The […]
Graph RAG, Graph RAG, Graph RAG! This term has become the talk of the town, and you might have come across it as well. But what exactly is Graph RAG, and what has made it so popular? In this article, we’ll explore the concept behind Graph RAG, why it’s needed, and, as a bonus, we’ll […]
When I was in high school and studied complex mathematics problems, I always used to think about why we were studying them or why they were useful. I was unable to understand and find their usage in the real world. Since machine learning is also a trending topic that many people want to explore, the […]
Stable Diffusion is trained on LAION-5B, a large-scale dataset comprising billions of general image-text pairs. However, it falls short of comprehending specific subjects and their generation in various contexts (often blurry, obscure, or nonsensical). To address this problem, fine-tuning the model for specific use cases becomes crucial. There are two important fine-tuning techniques for stable […]