Machine Learning Articles

Ellen Glover

Updated on November 01, 2024

An AI model is a program trained on data to eventually make its own decisions and predictions using new data — without human intervention. Here’s how AI models work, how they differ from machine learning and deep learning models and their common types.

Ellen Glover

Updated on October 31, 2024

Artificial intelligence enables machines to learn, solve problems and create like humans. It’s a complex field, with many technologies working in tandem. In this article, we’ll unpack the fundamentals of AI and explore how it is shaping our future.

Noah Topper

Updated on October 30, 2024

The bag of words model is a simple way to convert text into numerical data for natural language processing in machine learning. Our expert explains how it works.

Terrence J. Sejnowski

Updated on October 28, 2024

While some experts are pessimistic about AI innovations, some look forward to its altruistic use. Here’s what our expert has to say.

James Evans

Updated on October 25, 2024

Use RAG to customize large language model outputs.

Ellen Glover

Updated on October 25, 2024

Large language models are the backbone of generative AI, driving advancements in areas like content creation, language translation and conversational AI.

Kay Jan Wong

Updated on October 24, 2024

Trees are non-linear data structures that store data hierarchically and are made up of nodes connected by edges. Here’s how to implement it in Python using bigtree.

Parag Radke

Updated on October 24, 2024

Monte Carlo tree search (MCTS) is a heuristic search algorithm for decision processes. Here’s what you need to know.

Anas Al-Masri

Updated on October 23, 2024

Backpropagation is the neural network training process of feeding error rates back through a neural network to make it more accurate. Here’s what you need to know.