Quantum computing is a revolutionary field that leverages the principles of quantum mechanics to perform computations far beyond the capabilities of classical computers. In this blog, we will explore the fundamental concepts of quantum computing, providing detailed mathematical formulations and derivations for each topic. Quantum computing is an emergent field of computer science and engineering…
Missing values are a common issue in machine learning. This occurs when a particular variable lacks data points, resulting in incomplete information and potentially harming the accuracy and dependability of your models. It is essential to address missing values efficiently to ensure strong and impartial results in your machine-learning projects. In this article, we will…
Docker is the containerization platform that is used to package your application and all its dependencies together in the form of containers to make sure that your application works seamlessly in any environment which can be developed or tested or in production. Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. Docker is the world’s leading software container platform. It was launched in 2013 by…
Ever wanted to fine-tune a state-of-the-art AI art model like FLUX.1-dev but thought you needed expensive cloud GPUs? Think again. In this step-by-step guide, you’ll learn how to: ✔ Fine-tune FLUX.1-dev (12B parameters) on a single RTX 4090 (24GB VRAM) ✔ Reduce VRAM usage by 6x using QLoRA, gradient checkpointing, and 8-bit optimizers ✔ Achieve stunning style…
Matrices are omnipresent in math and computer science, both theoretical and applied. They are often used as data structures, such as in graph theory. They are a computational workhorse in many AI fields, such as deep learning, computer vision and natural language processing. Why is that? Why would a rectangular array of numbers, with famously…
What is Mixture of Experts? Mixture of Experts (MoE) is a technique that uses many different sub-models (or “experts”) to improve the quality of LLMs. Two main components define a MoE: Experts – Each FFNN layer now has a set of “experts” of which a subset can be chosen. These “experts” are typically FFNNs themselves. Router or gate…
Mixture of Experts (MoE) is a machine learning technique where multiple specialized models (experts) work together, with a gating network selecting the best expert for each input. In the race to build ever-larger and more capable AI systems, a new architecture is gaining traction: Mixture of Experts (MoE). Unlike traditional models that activate every neuron…
The journey to today’s sophisticated chatbots began decades ago with simple rule-based systems. The field of natural language processing (NLP) has undergone several revolutions: 1. Early Systems (1960s-1990s): ELIZA (1966) and PARRY (1972) used pattern matching to simulate conversation, but had no real understanding. 2. Statistical NLP (1990s-2010s): Systems began using probabilistic models and machine…
As one of the most popular programming languages out there, many people want to learn Python. But how do you go about getting started? In this guide, we explore everything you need to know to begin your learning journey, including a step-by-step guide and learning plan and some of the most useful resources to help…
Retrieval-Augmented Generation (RAG) enhances LLM text generation by incorporating external knowledge sources, making responses more accurate, relevant, and up-to-date. RAG combines an information retrieval component with a text generation model, allowing the LLM to access and process information from external databases before generating text. This approach addresses challenges like domain knowledge gaps, factuality issues, and hallucinations often…
