How Machine Learning Works: A Beginner’s Guide Machine Learning (ML) is a branch of artificial intelligence that enables computers to learn from data and make decisions without being explicitly programmed. This beginner-friendly guide breaks down the core concepts behind ML, including how models are trained, the difference between supervised and unsupervised learning, and how algorithms…
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,…
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…
What is Data Science? Data Science is an interdisciplinary field that blends various tools, algorithms, machine learning principles, and statistical techniques with the ultimate goal of extracting valuable insights from raw data. The primary focus of data science is to analyze large and complex data sets to uncover patterns, trends, and relationships that can…
Key Concepts Explained Large Language Models (LLMs): – LLMs are sophisticated AI systems designed to understand and generate human language. They are trained on vast amounts of text data, learning the structure and nuances of language, enabling them to perform tasks like translation, summarization, and conversation. Fine-Tuning vs. Pre-Training: – Pre-Training: In this…
Course on Large Language Models NOTE: You’re only meant to change code marked with “# TODO:” Table of Contents Setting Up API Key Configuration Connecting to OpenAI API Exploring the API Creating Chat Completions Understanding Completion Parameters Prompt Engineering Crafting Effective Prompts Strategies and Best Practices Advanced Techniques Utilizing Embeddings Function Calling in LLMs Extras…
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.
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.
