In recent years, two major breakthroughs have revolutionized the field of Large Language Models (LLMs): 1. 2017: The publication of Google’s seminal paper, (https://arxiv.org/abs/1706.03762) by Vaswani et al., which introduced the Transformer architecture – a neural network that fundamentally changed Natural Language Processing (NLP). 2. 2022: The launch of ChatGPT by OpenAI, a transformer-based chatbot…
Course Introduction: How Large Language Models (LLMs) Work What You Will Learn: The LLM Processing Pipeline In this course, you will learn how Large Language Models (LLMs) process text step by step, transforming raw input into intelligent predictions. Here’s a visual overview of the journey your words take through an LLM: Module Roadmap You will…
Creating a machine learning model might sound intimidating, but it’s a logical and repeatable process. In this guide, we’ll break down the steps involved in building your first machine learning model from scratch. Step 1: Define the Problem Before you write any code, ask: What do you want to predict or classify? Is it a…
Machine Learning (ML) is a subset of artificial intelligence (AI) that enables systems to learn from data and improve over time without explicit programming. ML algorithms are broadly categorized into different types based on their learning approach and application. Understanding these types is crucial for selecting the right model for your problem. In this blog,…
Convolutional Neural Networks (CNNs) have become the go-to architecture for image-related tasks in deep learning.
NVIDIA has firmly established itself as one of the most influential companies in the tech industry, particularly known for its leadership in the world of graphics processing units (GPUs).
Let’s break down AI, Machine Learning (ML), and Neural Networks in a structured way, covering key concepts, types of ML, and model architectures like Transformers, and their applications.
