Author(s): Alok Choudhary Originally published on Towards AI. Stop Wasting GPU Memory: Learn how LoRA reduces 175B parameters to just millions. Master efficient LLM fine-tuning with practical insights on rank and quantization. Fine-tuning large language models has become an essential part of …

Author(s): Alok Choudhary Originally published on Towards AI. Transform massive AI models into lightweight versions. Discover how quantization makes LLMs accessible on mobile and edge devices. In the world of Large Language Models (LLMs), two concepts are absolutely crucial for making these …

Author(s): Alok Choudhary Originally published on Towards AI. Everything about graph databases: Stop struggling with JOIN queries. Learn Cypher queries, vs SQL comparison, and building RAG applications with LangChain in 2026. In today’s data-driven world, the way we store and retrieve information …

Author(s): Alok Choudhary Originally published on Towards AI. A complete breakdown of hybrid search architecture, reciprocal rank fusion, and graph knowledge search for developers. When we build RAG (Retrieval-Augmented Generation) applications, the way we search and retrieve information makes a huge difference …

Author(s): Alok Choudhary Originally published on Towards AI. These are the actual questions from a recent hiring drive for Associate/Junior Data Scientist positions. All questions written in this story are real interview questions that were asked during a recent hiring assessment for …

Author(s): Alok Choudhary Originally published on Towards AI. LLM Poisoning! LLM poisoning is a way to deliberately corrupt an AI model by feeding it a small amount of bad data during its training. The core goal of a poisoning attack is to …

Author(s): Alok Choudhary Originally published on Towards AI. PyTorch Autograd: Automatic Differentiation Explained PyTorch Autograd is the backbone of PyTorch’s deep learning ecosystem, providing automatic differentiation for all tensor operations. This feature eliminates the need for manually deriving gradients, which is essential …

Author(s): Alok Choudhary Originally published on Towards AI. PyTorch Dataset and DataLoader: Theory, Concepts, and Workflow Efficient data handling is the backbone of deep learning. In PyTorch, the Dataset and DataLoader classes provide a structured way to load, preprocess, and iterate over …

Author(s): Alok Choudhary Originally published on Towards AI. PyTorch ANN Development: Building, Optimizing, and Hyperparameter Tuning Artificial Neural Networks (ANNs) are the foundation of modern deep learning. PyTorch makes it straightforward to design, train, and improve ANNs, while also offering flexibility to …

Author(s): Alok Choudhary Originally published on Towards AI. No subtitle available Long Short-Term Memory networks (LSTMs) are one of the most important architectures in deep learning for handling sequential data. Whether it’s language, time series, or speech, LSTMs solve a fundamental problem …

Author(s): Alok Choudhary Originally published on Towards AI. Unsupervised Machine Learning: A Complete Guide Machine Learning can be broadly divided into two categories: supervised learning and unsupervised learning. While supervised learning deals with labeled data, where the goal is to predict an …

Author(s): Alok Choudhary Originally published on Towards AI. LangChain Explained: A Beginner-Friendly Guide to Building LLM Applications Generative AI has grown far beyond being just a buzzword. Today, Large Language Models (LLMs) like GPT, Claude, and LLaMA are powering applications ranging from …

Author(s): Alok Choudhary Originally published on Towards AI. Anomaly Detection: A Comprehensive Guide Anomaly detection is one of those concepts in machine learning that looks deceptively simple but has a huge impact in real-world applications — from fraud prevention to equipment maintenance, …