Machine Learning Articles

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Ben Lamm Ben Lamm
Updated on July 12, 2022

A Proposal to Democratize AI

To ensure AI fulfills its potential, we must democratize the technology to avoid allowing it to be yet another driver of inequality. Here’s how we start.

Artem Oppermann Artem Oppermann
Updated on July 11, 2022

A Step-by-Step Explanation of Stochastic Policy Gradient Algorithms

In the final installment of this series, we’ll walk through stochastic policy gradients and AI agents in continuous action spaces.

Anupam Chugh Anupam Chugh
Updated on July 11, 2022

Is Kaggle Worth It for Data Scientists?

Kaggle can be a great way for newcomers to build data science skills. At a certain point, though, its artificial nature and emphasis on competition become harmful.

Kerry Halladay Kerry Halladay
Updated on February 15, 2022

For Users, Better AI Means More Personalization

Prepare for a world where the bots just get you.

Quinten Dol Quinten Dol
Updated on July 12, 2021

6 Cutting-Edge Applications of AI

How artificial intelligence is substantively reshaping industries, from e-commerce to insurance.

Nona Tepper Nona Tepper
Updated on July 09, 2021

How Artnome Uses Machine Learning to Predict the Price of an Artistic Masterpiece

Artnome is building the world’s largest database of paintings.

Tatum Hunter Tatum Hunter
Updated on July 08, 2021

Is an Open Web Still Possible?

Over the past decade, the internet has largely divided into walled gardens. Advocates want to bring the open web back.

Stephen Gossett Stephen Gossett
Updated on May 17, 2021

This GitHub Dev Is Using Deep Learning Text Generation to Write a Telenovela

Archetypal characters and well-established plot lines make telenovelas perfect for training an algorithm.

Stephen Gossett Stephen Gossett
Updated on January 14, 2021

Synthetic Data: How AI Uses Fake Data for Genuine Gains

Need more data to train your model? Make some.

Stephen Gossett Stephen Gossett
Updated on April 22, 2020

An Introduction to Machine Learning for Developers

You know a bit of R or Python. So how much statistics and domain expertise is necessary to really start training machine learning models?