ml5 - A friendly machine learning library for the web.
ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.
Machine Learning Glossary | Google for Developers
This glossary defines a wide range of machine learning terms, including those specific to TensorFlow and large language models.
AI, Apple and Google — Benedict Evans
As machine learning starts working, how does that change Google, Apple and the smartphone interface? What companies get reshaped around machine learning?
Google Research, 2022 & beyond: Language, vision and generative models
Posted by Jeff Dean, Senior Fellow and SVP of Google Research, on behalf of the Google Research community Today we kick off a series of blog posts ...
What is Machine Learning? | IBM
Machine learning is the subset of AI focused on algorithms that analyze and “learn” the patterns of training data in order to make accurate inferences about new data.
Distilling the Knowledge in a Neural Network
Our teams advance the state of the art through research, systems engineering, and collaboration across Google.
Introducing beginners to the mechanics of machine learning – Miriam Posner
Every year, I spend some time introducing students to the mechanics of machine learning with neural nets. I definitely don’t go into great depth; I usually only have one class for this. But I try to unpack at least some of the major concepts, so that ML isn’t quite such a black box.
Google AI Edge Gallery | Google for Developers
Designing machine learning systems: an iterative process for production-ready applications
"Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references."--Amazon.com
The interplay between machine learning and data minimization under the GDPR: the case of Google’s topics API
The rapid speed of digitalization and the continuous technological disruption have lead to different paradoxes and contradictions. With the widespread adop
The Great A.I. Awakening (Published 2016)
How Google used artificial intelligence to transform Google Translate, one of its more popular services — and how machine learning is poised to reinvent computing itself.
What Are Machine Learning Algorithms? | IBM
A machine learning algorithm is the procedure and mathematical logic through which an AI model learns patterns in training data and applies to them to new data.
Google for Developers Blog - News about Web, Mobile, AI and Cloud
Introducing Gemma 3n – the latest Google open model for accessible AI, featuring unique flexibility, privacy, and expanded multimodal capabilities on mobile devices.
Google Firebase Studio for AI app development (FREE)
