LLM Foundations Part 1: A Guide to Modern Language Models Introduction Welcome to a new series exploring the foundations of the technology that has captured the world’s imagination: Large Languag...

ML Foundations: A Guide to Natural Language Processing (NLP) Introduction Welcome back to our machine learning foundations series. So far, we’ve dealt mostly with numerical data. But what about t...

ML Foundations: From Neural Networks to Transformer Models Introduction In our series so far, we’ve explored powerful machine learning algorithms that form the bedrock of data science. Now, we ve...

ML Foundations: A Deeper Dive into Decision Trees Introduction In a previous post, we introduced Decision Trees and Random Forests, highlighting their intuitive, flowchart-like structure. We lear...

ML Foundations: The Naive Bayes Classifier Introduction In our journey through machine learning algorithms, we’ve seen models that find lines (Linear Regression), create S-curves (Logistic Regres...

ML Foundations: K-Nearest Neighbors (KNN) Introduction Welcome back to our machine learning foundations series! Today, we’re looking at one of the most intuitive and straightforward algorithms in...

ML Foundations: Unsupervised Learning and K-Means Clustering Introduction Throughout our machine learning series, we’ve focused on Supervised Learning. In supervised learning, our data is labeled...

ML Foundations: Support Vector Machines (SVMs) Introduction In our machine learning series, we’ve explored models that classify data in different ways. Logistic Regression finds a line that separ...

ML Foundations: Decision Trees and Random Forests Introduction So far in our series, we’ve explored models that are fundamentally mathematical, like Linear and Logistic Regression. Now, we’re goi...

ML Foundations: Preprocessing Data for Machine Learning Introduction You’ve learned about powerful machine learning models like Linear and Logistic Regression. But in the real world, data is rare...