Large Language Models (LLMs) come in various optimized forms, each designed for specific use cases, efficiency, and performance. In this guide, we’ll explore the different types of LLMs (like distilled, quantized, sparse, and MoE models) and how they are trained. In the fast-evolving world of Large Language Models (LLMs), different model types serve different performance and deployment goals…
Data science and machine learning require powerful hardware to handle complex computations, large datasets, and AI model training. Whether you’re a student or a professional, choosing the right laptop is crucial for efficiency and future-proofing your investment. Introduction: Why Machine Learning Needs Serious Hardware Machine Learning (ML) involves training algorithms on large datasets to recognize…
Welcome to the future — a world where machines not only follow instructions but learn from data! Whether you’re a tech enthusiast, a student, or a curious mind, this blog post will give you a gentle introduction to the fascinating world of Machine Learning (ML). What is Machine Learning? Machine Learning is a subset of…
As a candidate, I’ve interviewed at a dozen big companies and startups. I’ve got offers for machine learning roles at companies including Google, NVIDIA, Snap, Netflix, Primer AI, and Snorkel AI. I’ve also been rejected at many other companies. As an interviewer, I’ve been involved in designing and executing the hiring process at NVIDIA and…
Convolutional Neural Networks (CNNs) are one of the most powerful tools in deep learning, particularly for tasks related to computer vision.
Convolutional Neural Networks (CNNs) have become the go-to architecture for image-related tasks in deep learning.
Machine Learning
is a vast and intricate field that requires an understanding of key concepts from mathematics, statistics, programming, and data science. Let’s go through everything step-by-step, from the fundamental maths to the essential skills required to build ML models.
