Machine Learning Articles

Artem Oppermann

Updated on May 23, 2025

In this four-part series, I’ll show you how the Markov decision process works and the mathematical theory you need to know to understand deep reinforcement learning.

Sara A. Metwalli

Updated on May 23, 2025

What is quantum computing and how can you break into the field? Use these resources to get started.

Parul Pandey

Updated on May 22, 2025

Image processing in Python involves using Python to analyze and manipulate digital images to improve quality or extract information. Here’s an overview of common Python libraries used for image processing tasks.

Zijian Feng

Updated on May 22, 2025

ResNet (Residual Network) architecture is a type of artificial neural network that enables the flow of gradients through skip connections, which mitigates vanishing gradients and improves trainability in very deep convolutional neural networks.

Mór Kapronczay

Updated on May 22, 2025

A language model conducts a probability distribution over words or word sequences. Here’s more on what language models can do, their types, evolution and future outlook.

Javaid Nabi

Updated on May 22, 2025

Multiclass classification is a machine learning task that involves classifying data into one of three or more classes. Here’s what you need to know.

Luuk Derksen

Updated on May 22, 2025

T-distributed stochastic neighbor embedding (t-SNE) is a non-linear dimensionality reduction technique used to visualize high-dimensional data in a low-dimensional 2D or 3D space. Here's how to apply it in Python.

Abhijeet Pujara

Updated on May 22, 2025

MobileNet is a mobile-first class of convolutional neural network (CNN) that was open-sourced by Google and provides a starting point for training classifiers through a lightweight model.

Sean Benhur

Updated on May 22, 2025

A Siamese neural network (SNN) is a type of neural network architecture that contains two or more identical sub-networks with the same parameters and weights. SNNs can make predictions using only a few images per class.

Bharath Krishnamurthy

Updated on May 22, 2025

Advancements in artificial intelligence and deep learning have led to the rapid development of chess engines. Here’s a look at the history of chess AI, how it continues to evolve and how developers can get started in building their own chess AI engines.