The rise of large language models (LLMs) like GPT-4, Claude, LLaMA, and PaLM has revolutionized the field of artificial intelligence. However, using these models to build real-world applications that are context-aware, interactive, and robust requires more than just sending prompts and receiving text responses. This is where LLM frameworks like LangChain come in. These frameworks … Read more
Generative AI, or Gen AI, is rapidly reshaping how we interact with technology, unleashing a wave of creativity, automation, and intelligence across industries. From writing and designing to coding and drug discovery, generative AI models can produce content that once required human intelligence, creativity, and domain expertise. If you’re wondering how generative AI is used … Read more
Faiss (Facebook AI Similarity Search) is a powerful library developed by Facebook AI Research that is widely used for efficient similarity search and clustering of dense vectors. If you’re working with large-scale vector data, Faiss can significantly speed up your nearest neighbor search tasks, especially when combined with GPU acceleration. While Faiss installation on Linux … Read more
Choosing the right loss function is one of the most critical steps in building a successful machine learning model. It directly affects how the model learns, how fast it converges, and how well it generalizes to unseen data. If you’re wondering how to choose a loss function for your machine learning task, this guide will … Read more
In the world of machine learning, loss functions are a core component of model training. They act as a guide for learning by quantifying how far off a model’s predictions are from actual results. The goal of any machine learning model is to minimize this loss, which in turn helps it make better predictions. Without … Read more
In recent years, machine learning in cloud computing has become a transformative force in how businesses build, deploy, and scale intelligent systems. Whether you’re a data scientist, developer, or business leader, understanding how cloud computing supports machine learning can help you harness its full potential. In this in-depth guide, we’ll explore what machine learning in … Read more
Deep learning is one of the most exciting and impactful fields in technology today. From powering self-driving cars to enabling voice assistants and automating medical diagnostics, deep learning is transforming industries. If you’re asking, “How do I get started in deep learning?”, you’re in the right place. This beginner-friendly guide will walk you through the … Read more
Getting started with machine learning can feel intimidating, especially if you’re new to Python or data science. But don’t worry! This guide will walk you through a basic machine learning Python example from start to finish. You’ll learn how to build a simple predictive model using real data, and along the way, you’ll also pick … Read more
Machine learning (ML) is everywhere these days — from recommending your next movie to powering self-driving cars. And guess what? Learning it doesn’t have to be complicated or intimidating. Thanks to Python’s simplicity and an amazing ecosystem of libraries, it’s never been easier to get started. If you’ve been curious about diving into machine learning … Read more
When working with large-scale vector similarity search, performance and scalability become crucial. That’s where Faiss, an open-source library developed by Facebook AI Research, stands out. Designed for efficient similarity search and clustering of dense vectors, Faiss is widely adopted in applications like recommendation systems, image retrieval, semantic search, and large language model (LLM) embeddings. But … Read more
