Curated resources about how you might use artificial intelligence techniques to make your software smarter, your users happier, and your business better.
“Artificial intelligence is a broad set of software capabilities that make your software smarter. We think it’s going to have as broad (and maybe broader) an impact on software as relational database technologies: It’s hard to think of a company whose products or services you use today that aren’t enabled by databases.
We’re in the very early years of putting AI in all our software in the same way we put databases in all our software, and this trend will unfold over decades, not months or even years. AI is the new relational database, about to get into every important piece of software we write.” Frank Chen
"More often than not, companies are not ready for AI. Maybe they hired their first data scientist to less-than-stellar outcomes, or maybe data literacy is not central to their culture. But the most common scenario is that they have not yet built the infrastructure to implement (and reap the benefits of) the most basic data science algorithms and operations, much less machine learning."
Andrew Ng is VP & Chief Scientist of Baidu; Co-Chairman and Co-Founder of Coursera; and an Adjunct Professor at Stanford University. In 2011 he led the development of Stanford University’s main MOOC (Massive Open Online Courses) platform and also taught an online Machine Learning class to over 100,000 students, leading to the founding of Coursera. Ng’s goal is to give everyone in the world access to a great education, for free. Today, Coursera partners with some of the top universities in the world to offer high quality online courses, and is the largest MOOC platform in the world.
Andrew Ng – Personal website →
Andrew Ng – Machine Learning courses on Coursera →
Andrew Ng – Deep Learning courses on Coursera →
Andrew Ng – Harvard Business Review →
Artificial Intelligence (AI) is a set of computer science techniques that, as Stanford professor Andrew Ng is fond of saying, gives your software super powers. This microsite is intended to help newcomers (both non-technical and technical) begin exploring what's possible with AI. We've met with hundreds of Fortune 500 / Global 2000 companies, startups, and government policy makers asking: "How do I get started with artificial intelligence?" and "What can I do with AI in my own product or company?"
See more at aiplaybook.a16z.com →
GitHub – Getting started with machine learning
With the world’s biggest collection of open source data, GitHub’s Data Science Team has just started exploring how we can use machine learning to make the developer experience better. I see machine learning shaping experiences around me every day, and I’m excited about what’s to come in applying it to create more useful, predictive technologies. In this collection, I'll share the basics of machine learning, along with some related resources and projects for people who are getting started with it.
See more at github.com/collections/machine-learning →
Apple Machine Learning Journal
Welcome to the Apple Machine Learning Journal. Here, you can read posts written by Apple engineers about their work using machine learning technologies to help build innovative products for millions of people around the world. If you’re a machine learning researcher or student, an engineer or developer, we’d love to hear your questions and feedback.
See more at machinelearning.apple.com →
We're heading towards a future with semi and fully autonomous predicted User Experiences. The aim of this project is to create an Anticipatory Design Manifesto at which we define guiding design principles and mitigate ethical challenges.
See more at anticipatorydesign.com →
Facebook – Applied Machine Learning
Machine learning is essential to Facebook. It helps people discover new content and connect with the stories they care the most about. Our applied machine learning researchers and engineers develop machine learning algorithms that rank feeds, ads and search results, and create new text understanding algorithms that keep spam and misleading content at bay. New computer vision algorithms can “read” images and videos to the blind and display over 2 billion translated stories every day, speech recognition systems automatically caption the videos that play in your news feed, and we create new magical visual experiences such as turning panorama photos into fully interactive 360 photos.
See more at facebook.ai →
fast.ai is dedicated to making the power of deep learning accessible to all. Deep learning is dramatically improving medicine, education, agriculture, transport and many other fields, with the greatest potential impact in the developing world. For its full potential to be met, the technology needs to be much easier to use, more reliable, and more intuitive than it is today.
See more at fast.ai →
A visual introduction to machine learning
In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.
See more at r2d3.us/visual-intro-to-machine-learning-part-1 →
NVIDIA AI Podcasts
Artificial Intelligence has been described as “Thor’s Hammer“ and “the new electricity.” But it’s also a bit of a mystery – even to those who know it best. We’ll connect with some of the world’s leading experts in artificial intelligence, deep learning, and machine learning to explain how it works, how it’s evolving, and how it intersects with every facet of human endeavor, from art to science. We release new episodes every week.
AI Podcasts →
What is Artificial Intelligence? Mike Loukides and Ben Lorica examine factors that have made AI a hot topic in recent years, today's successful AI systems, and where AI may be headed.
What is Artificial Intelligence? →
The latest insights, ideas, and tools for building solutions that rely on machine intelligence →