Tomorrow, August 11th, Google's Brain Team will be answering questions submitted in this Reddit thread on the topic of machine learning. It is an AMA, ask me anything, session and it was introduced as "AMA: We are the Google Brain team. We'd love to answer your questions about machine learning." Now, this is not simply about RankBrain but all of Google's machine learning efforts across all their products and services. This includes, Google said, RankBrain for Google Search, SmartReply for GMail, Google Photos, Google Speech Recognition and more.

NIPS (which stands for "Neural Information Processing Systems") is an annual conference on machine learning and computational neuroscience, and papers presented there reveal what experts in the field are working on. Conveniently, you can find the data from the 2015 conference from Kaggle's NIPS 2015 Papers page. Let's load the data downloaded from Kaggle to the current folder. I also wrote a script nips2015_parse_html in order to parse the HTML file "accepted_papers.html" We can visualize which organization the authors of accepted papers belong to using graphs.

The fastest way to get good at applied machine learning is to practice on end-to-end projects. In this post you will discover how to work through a regression problem in Weka, end-to-end. Step-By-Step Regression Machine Learning Project Tutorial in Weka Photo by vagawi, some rights reserved. This tutorial will walk you through the key steps required to complete a machine learning project in Weka. Weka is the best platform for beginners getting started in applied machine learning.

Microsoft India today announced the winners of the 24 hour hackathon, held as part of the first Machine Learning & Data Sciences (ML&DS) Conference. Team Builders won the grand prize, while Eavesdroppers and NHacks emerged as the first and second runners up respectively by creating applications to address challenges in the field of agriculture, call center management and human behavior. The hackathon invited students and early-stage developers to work in teams to build intelligent, working applications with the help of Microsoft Cognitive Services, Microsoft Bot Framework and Microsoft R Services. The top three teams won cash prizes worth INR 50,000, INR 40,000 and INR 30,000 for developing solutions fulfilling parameters on design, innovation, foreseeable impact and marketability. In addition to the cash awards, the student participants from the winning teams will also be offered interviews for internships and full time positions at Microsoft India (R&D) Pvt. Ltd. "Microsoft has the vision, strategy and talent to democratize data and machine learning and use it to realize our mission to empower every individual and organization on the planet to achieve more. The hackathon was designed to spark curiosity among diverse talent to develop applications using our services and demonstrate the versatility and potential of using the platform. It has also shown us how Microsoft's APIs could help scale ideas with global relevance in a very short time," said Anil Bhansali, Managing Director, Microsoft India (R&D) Pvt. Ltd.

Global software major Microsoft on Monday invited developers to use its machine learning and data platforms for building digital products and solutions to transform businesses and drive inclusive growth. "Our ambition is to democratise access to new technologies so that software developers can build, innovate and transform the world with them," said Microsoft data group Vice President Joseph Sirosh at a conference on machine learning and data sciences in India. Noting that cloud-based services for machine learning and big data, coupled with the Internet of Things (IoT) have the potential to revolutionise every aspect of life, including sports, healthcare, education and even government, he said the company's unique platforms such as the Cortana Intelligence suite were helping customers to harness the power of artificial intelligence. The two-day conference is aimed at exploring the possibilities with big data, machine learning, artificial intelligence and open source technologies in enabling platforms, intelligent apps, services and experiences to accelerate economic growth, empower people and drive real impact. Demonstrating the power of data analytics, Microsoft unveiled an Azure machine learning-based approach for calculating target scores in weather-interrupted T-20 cricket matches.

The reality did not live up to the expectations set by science fiction. Accordingly, for many years, the majority of people's understanding of A.I. was confined to university laboratories, corporate skunk works, research parks, and that movie with Haley Joel Osment and Jude Law. Attempts to introduce A.I. products and services into the marketplace and for the broader benefits of society were ill-fated. Computing power was insufficient, and the abundance of structured data -- let alone a knowledge of what to do with said data -- was not yet upon us. A.I. has been on the cusp of the mainstream for the past 40 years, but 2016 is the year it's become a buzzword -- incorporating machine learning, natural language processing, voice recognition, and data mining, to name a few technologies.

The Global Artificial Intelligence & Robotics Summit has opened in the southern Chinese city of Shenzhen. Our reporter Ge Yunfei went to China's southern technology center to find out more about the potential of the budding industry. The success of Alpha Go in defeating the human mind has aroused the world of artificial intelligence. But at the Global Artificial Intelligence & Robotics Summit in Shenzhen, it's limitations have been projected. Michael Wooldrige -- who is leading a cooperation initiative between Oxford University and Google on artificial intelligence -- said although Alpha Go is unique in its own right, it's not THAT smart.

Due to similar problems, some even prefer to steer away from AI, preferring to simply call it machine intelligence. It's simply no longer artificial intelligence in as much as technically it remains so. Looking beyond these marketing pitches, there are some really serious developments of seismic proportions that are taking place around the idea of artificial intelligence. What is even more intriguing is that the developments taking place around AI have potentially far reaching consequences on just about every soul on the planet.

Intel is now set to compete against NVIDIA in the deep learning and AI arena, acquiring AI startup Nervana. Nervana specializes in processor-based "deep learning as a service" through technology like its upcoming Nervana Engine, a dedicated AI hardware accelerator due out in early 2017. Intel wants to utilize Nervana's expertise to help its AI performance on its Xeon and Xeon Phi processors, as it sees AI as a big future for the company. NVIDIA is already knee deep in deep learning, with self-driving cars, AI, and more. NVIDIA could face serious competition in the deep learning and AI space if Nervana can help Intel tune its processors for machine learning tasks.

The opportunity for fintech companies to disrupt traditional financial institutions is best observed today in millennials' habits. Millennials have a clear preference for accomplishing tasks through digital applications and services -- something fintech companies are better at providing than banks in terms of speed and personalization. More disturbing, Gen Y customers are far less loyal to their banks: only 45% of North American millennials said they plan to stick with their current bank, compared to 85% of North American respondents from all other age groups. While banks have steadily built up their online and mobile channels -- in part to appeal to millennials -- the products and services they offer in those channels are built on top of legacy systems and fail to provide the level of speed and personalization millennials expect. A customer might be able to deposit a check from anywhere with their mobile device, but it can take several days for that deposit to post to the user's account.