In 1948, Claude Shannon published a paper that changed how we think about information forever.

  Decision tree-based models for predictive machine learning tasks like classification and regression are undoubtedly rich in advantages — such as their ability to capture

This article is divided into two parts; they are: • Picking a Dataset • Training a Tokenizer To keep things simple, we’ll use English text

Decision tree-based models in machine learning are frequently used for a wide range of predictive tasks such as classification and regression, typically on structured, tabular

You’ve learned about

LLMs

A good language model should learn correct language usage, free of biases and errors.

Building machine learning models in high-stakes contexts like finance, healthcare, and critical infrastructure often demands robustness, explainability, and other domain-specific constraints.

When large language models first came out, most of us were just thinking about what they could do, what problems they could solve, and how