A new study in The Lancet found that a deep-learning algorithm was able to detect vision-threatening retinopathy with 94.7% accuracy.

Part 1 of a 3-part blog series on advances in contrastive learning.

by Jacob Buckman and Carles Gelada This post is part of a series on bad abstractions in machine learning. For context on why we are writing these, read Abstraction Enables Thought. Bad Abstraction: There are two types of machine learning models. Discriminative…

Welcome to Fennel AI’s blog! We publish high quality technical content on building realtime recommendation systems. Subscribe for free to get all posts delivered straight to your inbox. Training a collaborative filtering based recommendation system on a toy…

Data apps for data scientists and data analysts.

RelationalAI wants to change the way data-driven applications are built by combining a database system with a knowledge graph.

Synthetic data is artificially annotated information that is generated by computer algorithms or simulations, commonly used as an alternative to real-world data.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

By Been Kim, Google Research, Brain Team

Here comes the Part 3 on learning with not enough data (Previous: Part 1 and Part 2). Let’s consider two approaches for generating synthetic data for training.

Augmented data. Given a set of existing training samples, we can apply a variety of augmentation…

The fundamentals of Data Science include computer science, statistics and math. It’s very easy to get caught up in the latest and greatest…

Developing good predictive models hinges upon accurate performance evaluation and comparisons. However, when evaluating machine learning models, we typically...

Understanding The Properties of Data

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Some include code and exercises