@machinelearnbot


[R] AlphaGo Zero: Learning from scratch DeepMind • r/MachineLearning

@machinelearnbot

Our program, AlphaGo Zero, differs from AlphaGo Fan and AlphaGo Lee 12 in several important aspects. First and foremost, it is trained solely by self-play reinforcement learning, starting from random play, without any supervision or use of human data. Second, it only uses the black and white stones from the board as input features. Third, it uses a single neural network, rather than separate policy and value networks. Finally, it uses a simpler tree search that relies upon this single neural network to evaluate positions and sample moves, without performing any MonteCarlo rollouts.


Machines learn new ways of learning - CIFAR

@machinelearnbot

Intelligent machines have learned to read and write, recognize images, and predict dangerous mutations. But how does a machine learn to learn in the first place? The art of'learning to learn' (or meta-learning) is now widely recognized as a cornerstone of artificial intelligence research. Over the last few years, the idea of using data to learn the learning algorithms has gained momentum -- and massive computational resources and datasets have made it possible. In 2016, Nando de Freitas, a Senior Fellow in CIFAR's Learning in Machines & Brains program, demonstrated a novel approach to learning to learn.


SAS continues to innovate, delivering AI capabilities on its modern, in-memory platform

@machinelearnbot

Analytics leader SAS is helping customers gain more value from data with SAS Viya products, extending the value from the SAS Platform. These newest advances, such as embedded artificial intelligence (AI) capabilities, will further address the needs of organisations that are making analytics core to their business. A variety of industries, countries and organisation sizes have embraced SAS Viya products. With SAS, data scientists, analysts, developers, IT, domain experts and executives can all generate data-driven insights – from the same, consistent data, fostering greater collaboration and driving innovations faster. SAS continues to deliver new capabilities, such as image recognition, deep learning and natural language understanding into the SAS Platform.


Woebot: AI for mental health – Andrew Ng – Medium

@machinelearnbot

I'm thrilled to announce I am joining Woebot's board of directors as its Chairman. I will be assisting its CEO, Alison Darcy, and the company in its mission to build a chatbot that will help the millions of people who struggle with their mental health. Depression is the leading global cause of disability. You probably have friends with depression that don't talk about it. It is stigmatized, which only deepens their anguish.


horovod

@machinelearnbot

TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details--for instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA's CUDA toolkit. Additionally, TensorFlow has end-to-end support for a wide variety of deep learning use cases, from conducting exploratory research to deploying models in production on cloud servers, mobile apps, and even self-driving vehicles.


Health Predictions - The Future of Healthcare

@machinelearnbot

In the latest of our Predictions series we take a look at what the future of healthcare will look like. Could artificial intelligence and smart technology improve every stage of our lives? We look at how the future of healthcare will affect us from birth including wearable tech and the internet of things to capturing baseline health data we can use to monitor our health as we grow older. From womb to tomb Health scanning and data will become ever present in our lives – even from the very start of life. Before birth, scanning will take place in the womb which will create a basic profile of a person's health and create treatment plans from the very start.


Senior Software Engineer - AI / Machine Learning / Data Science

@machinelearnbot

This position is located in Cupertino, California. Who is SugarCRM SugarCRM enables businesses to create extraordinary customer relationships with the most empowering, adaptable and affordable customer relationship management (CRM) solution on the market. We are the industry's leading company focused exclusively on customer relationship management. Helping our clients build a unique customer experience through great customer relationships is our sole focus. Recognized by leading market analysts as a CRM visionary and innovator, Sugar is deployed by more than 2 million individuals in over 120 countries and 26 languages.



Complete Intro into Natural Language Processing – APJama – Medium

@machinelearnbot

You and I speak a language. Most people speaks at least one language. We've probably not had to think very hard about how we've learnt this language. The jury is still out on this, but we've got some pretty good ideas about how this is done. For Chomsky and others, humans are equipped with an innate ability to learn languages.


At GitHub, JavaScript rules in usage, TensorFlow leads in forks

@machinelearnbot

JavaScript is the most-popular language on GitHub, based on pull requests from the popular code-sharing site. Since September 2016, there have been 2.3 million pull requests for JavaScript, GitHub reports. Following web development staple JavaScript was Python, with 1 million requests, and Java, with 986,000 requests. Python displaced Java as the second-most-popular language on GItHub. Also improving its lot greatly in 2017 was TypeScript, Microsoft's typed superset of JavaScript, which had 207,000 pull requests, almost four times as many requests as it had the year before.