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Machine Learning Crash Course: Part 1
Machine Learning at Berkeley is a student organization at UC Berkeley. Click to read ML@B Blog, by Machine Learning at Berkeley, a Substack publication with thousands of subscribers.
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The latest blog posts to take off on Hacker News. 153 posts.
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Machine Learning Crash Course: Part 2
Machine Learning at Berkeley is a student organization at UC Berkeley. Click to read ML@B Blog, by Machine Learning at Berkeley, a Substack publication with thousands of subscribers.
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A Guide to Deep Learning
YerevaNN /jɛɾɛvɑnˈɛn/ is a machine learning research center based in Yerevan, Armenia.
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The Most Popular Language for Machine Learning
IBM Developer is the source for hands-on training and in-demand learning on relevant technologies such as generative AI, data science, Java, and more.
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Start building Actions on Google
The Google Assistant brings together all of the technology and smarts we've been building for years, from the Knowledge Graph to Natural Language Processing. To be a truly successful Assistant, it should be able to connect users across the apps and services in their lives. This makes enabling an ecosystem where…
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Major advancements in Deep Learning in 2016
Deep Learning has been the core topic in the Machine Learning community the last couple of years and 2016 was not the exception. In this article, we will go through the advancements we think have contributed the most (or have the potential) to move the field forward and how organizations and the community are making…
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Open sourcing Embedding Projector: a tool for visualizing high dimensional data
Posted by Daniel Smilkov and the Big Picture group Recent advances in Machine Learning (ML) have shown impressive results, with applications rangin...
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Open-sourcing DeepMind Lab
DeepMind's scientific mission is to push the boundaries of AI, developing systems that can learn to solve any complex problem without needing to be taught how.
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What makes Bach sound like Bach? New dataset teaches algorithms classical music
MusicNet is the first publicly available large-scale classical music dataset designed to allow machine learning algorithms to tackle everything from automated m
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Artificial Intelligence Generates Christmas Song from Holiday Image
Researchers from University of Toronto developed an AI system that creates and then sings a Christmas song based by analyzing the visual components of an uploaded image. With the help of CUDA…
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Amazon Rekognition – Image Detection and Recognition Powered by Deep Learning
What do you see when you look at this picture? You might simply see an animal. Maybe you see a pet, a dog, or a Golden Retriever. The association between the image and these labels is not hard-wired in to your brain. Instead, you learned the labels after seeing hundreds or thousands of examples. Operating […]
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Amazon Polly – Text to Speech in 47 Voices and 24 Languages
As I was getting ready to write this post, I thought back to my childhood (largely spent watching TV) and some of the popular computer and robot voices of the 1960’s and 1970’s. In just a few minutes, pleasant memories of HAL-9000, B9 (Lost in Space), the original Star Trek Computer, and Rosie (from The […]
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Amazon Lex – Build Conversational Voice and Text Interfaces
While computers that talk are great, computers that listen and respond are even better! If you have used an Amazon Echo, you know how simple, useful, and powerful the Alexa-powered interaction model can be. Today we are making the same deep learning technologies (ASR – Automatic Speech Recognition NLU – Natural…
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TensorFlow 0.12 adds support for Windows
Native support for TensorFlow on Windows was one of the first requests we received after open-sourcing TensorFlow. Although some Windows users have managed to run TensorFlow in a Docker container, we wanted to provide a more complete experience including GPU support.
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Intel Unveils Strategy for State-Of-the-Art Artificial Intelligence
Intel Newsroom delivers the latest news, announcements, and updates. Stay informed on Intel innovations.
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Zero-Shot Translation with Multilingual Neural Machine Translation System
Posted by Mike Schuster (Google Brain Team), Melvin Johnson (Google Translate) and Nikhil Thorat (Google Brain Team)In the last 10 years, Google Tr...
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Reinforcement learning with unsupervised auxiliary tasks
Our primary mission at DeepMind is to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught how. Our reinforcement learning agents have achieved breakthroughs in Atari 2600 games and the game of Go. Such systems, however, can require a lot of data and a…
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How Quid uses deep learning with small data
Enhance your consumer & market intelligence knowledge with our resource library. Discover the role of Generative AI in transforming the digital landscape.
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OpenAI and Microsoft
We’re working with Microsoft to start running most of our large-scale experiments on Azure.
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Found in translation: More accurate, fluent sentences in Google Translate
In 10 years, Google Translate has gone from supporting just a few languages to 103, connecting strangers, reaching across language barriers and even helping people find …
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GPUs for Google Cloud Platform
CPU-based machines in the cloud are terrific for general purpose computing, but certain tasks such as rendering or large-scale simulations are much faster on specialized processors. Graphics Processing Units (GPUs) contain hundreds of times as many computational cores as CPUs and are great at accelerating risk…
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RAISR Sharp Images with Machine Learning
Posted by Peyman Milanfar, Research Scientist Everyday the web is used to share and store millions of pictures, enabling one to explore the world, ...
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Embed, encode, attend, predict: the new deep learning formula for NLP models
Over the last six months, a powerful new neural network playbook has come together for Natural Language Processing. The new approach can be summarised as a simple four-step formula: embed, encode, attend, predict. This post explains the components of this new approach, and shows how they're put together in two recent…
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