Start Here    

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...
mladvocate
3 min read

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...
mladvocate
6 min read

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...
mladvocate
2 min read

Welcome to Machine Learning Advocate

ChatGPT answering your questions, your iPhone sorting photos by face, Netflix deciding what to show you next. All of it is...
mladvocate
43 sec read

Foundations    

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...
mladvocate
2 min read

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...
mladvocate
2 min read

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...
mladvocate
2 min read

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...
mladvocate
10 min read

Mental Models    

Bias vs. Variance: Why Your ML Model Can’t Have It All

For years, every time I fixed one problem with my models, I created another one. Make the model more sophisticated to...
mladvocate
3 min read

Training vs. Testing: Why Your Model Needs to Prove Itself on New Data

Does this sound familiar? You’re tutoring a student for an upcoming math test. You help them solve dozens of practice problems...
mladvocate
5 min read

Prediction vs Inference: Different Goals in ML Analysis

Some machine learning applications can make accurate recommendations but can’t explain the reasoning. Others provide clear explanations but aren’t quite as...
mladvocate
2 min read

Classification vs Regression: Predicting What vs. How Much

In our previous post, we explored supervised vs. unsupervised learning. Now we’re diving into another fundamental choice you’ll face in every...
mladvocate
5 min read

Supervised vs Unsupervised Learning: The Two Main Ways Machines “Learn”

Remember learning to ride a bike? Some of us had a parent running alongside, holding the seat and shouting guidance: “Pedal...
mladvocate
5 min read

Mathematics and Statistics    

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...
mladvocate
1 min read

ML in the Wild    

Machine Learning in the NBA: Player Tracking and Injury Prevention

Every NBA arena has cameras mounted in the catwalks that track every player and the ball at 25 frames per second....
mladvocate
2 min read

MLB Statcast and Machine Learning: How Data Transformed Baseball

Baseball has always been a numbers game. Batting averages, earned run averages, and RBIs have been part of the sport for...
mladvocate
2 min read

How Formula 1 Teams Use Machine Learning to Win Races

In Formula 1, milliseconds decide races. The cars generate massive amounts of data, around 400 GB per race from sensors tracking...
mladvocate
1 min read

Machine Learning in Sports: How AI Predicts NFL Tackles

This is the first post in the “ML in the Wild” series, where we look at specific machine learning applications in...
mladvocate
1 min read

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