Machine Learning Math: Start Simple, Learn as You Go
Last year a data analyst I work with told me she’d closed a machine learning tutorial after the first page. Too many equations. She assumed the field wasn’t for her. She was wrong, but I understood why she felt that way. Most ML education starts with partial derivatives and linear algebra before you’ve even seen […]
Machine Learning Foundations Part 4: Understanding Hardware
When your phone slows down because too many apps are open, it lags, gets warm, and everything takes twice as long to load. Machine learning has the same problem, just at a much bigger scale. The algorithms and models we’ve covered in this series all need physical computing power to run, and the type of […]
Machine Learning Foundations Part 3: Understanding Algorithms
This is Part 3 of our Foundations series. In Part 1, we covered data. In Part 2, models. Now we’re looking at algorithms: the methods that find patterns in data and produce models. What Is an Algorithm? An algorithm is a set of steps for solving a problem. A recipe is an algorithm. Driving directions […]
Machine Learning Foundations Part 2: Understanding Models
This is Part 2 of our Foundations series. In Part 1, we covered data. Now we’re looking at models: what they are, what types exist, and how they represent patterns in data. What Is a Model? Think about how a child learns what a dog is. At first, everything with four legs might be “dog.” […]
Machine Learning Foundations Part 1: Understanding Data
Data: The Foundation of Machine Learning This is the first post in a 4-part series that takes you behind the scenes of how machines learn. We’ll explore the fundamental building blocks of machine learning: the data, the models, the algorithms, and the hardware that powers today’s technologies. By the end of this series, you’ll have […]
Making Sense of Data: From Statistics to AI
In today’s data-driven world, the terms statistics, data science, machine learning, and artificial intelligence are often used interchangeably, yet each field has distinct characteristics and applications. From statistics forming the mathematical foundation to AI’s broad vision of intelligent systems, these disciplines work.
From Mendel’s Peas to ChatGPT: A History of Machine Learning
The journey of machine learning is a captivating tale that spans centuries, from the humble pea plants in a 19th-century monastery garden to the cutting-edge Transformer models powering today’s AI breakthroughs. This evolutionary path, marked by visionary thinkers, groundbreaking discoveries, and paradigm-shifting advancements, has transformed the way we approach complex problems and unravel the mysteries of intelligent systems.
Join us as we embark on a fascinating exploration of the key milestones, pioneering figures, and seismic shifts that have shaped the dynamic field of machine learning. From the foundational work of Gregor Mendel and Alan Turing to the revival of neural networks through backpropagation and the recent Transformer revolution, this blog post will take you on a journey through time, revealing the integral connections between the past, present, and future of this transformative technology.
What is Machine Learning? A Beginner’s Guide
Your phone’s camera doesn’t just take pictures anymore. It decides when to use night mode, adjusts focus automatically, and can even remove photobombers. Nobody programmed a rule for every possible lighting condition. Instead, the software learned what a good photo looks like by studying millions of them. That’s machine learning. And once you see it, […]
Welcome to Machine Learning Advocate
Machine Learning is everywhere. It decides which loan applications get approved, which medical scans get flagged for review, which play an NFL defense is likely to run on third and six. Existing blogs, tutorials, and courses tend to fall into one of two categories: technically impenetrable, or so simplified they are basically wrong. This site […]