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Machine Learning

Machine learning is Big Data being used at its most extreme level, processing vast and disparate data sets at a machine level to find patterns buried within, producing insights beyond human recognition.

Machine Learning

Machine learning- to put it mildly- is an incredibly broad and varied field, with multitudes of applications. Thus, writing a list entitled “10 Machine Learning Experts You Need to Know” proves challenging for a number of reasons. Firstly, I’ve restricted my ten picks to those currently working in the field-

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Machine LearningNews

To infer the causal impact that a designed market intervention has exerted on an outcome metric over time has been a significant issue in econometrics and marketing. Last week, Google open sourced CausalImpact – a tool that will assist analysts in monitoring any measurable outcome with regards to products or

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Machine LearningNews

Scientists at the Binghamton University have developed a predictive algorithm through analysing tweets to forecast an individual’s behaviour well in advance. Systems scientists at the Binghamton University, Sang Won Yoon and Sarah Lam working alongside Nathan Gnanasambandam, also Binghamton alumnus and a senior researcher at the Xerox Research’s Palo Alto

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Machine LearningNews

Text mining innovators-in-the-making MonkeyLearn have finally opened their beta version for the public to sign up. The announcement came at TechCrunch Disrupt in San Francisco, on Monday. The cloud-based artificial intelligence platform intends to transform text mining the same way WordPress made content creation available to all, reports VentureBeat. CEO

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Machine LearningNews

Pioneers in machine learning for visual recognition and founders of facial recognition software developer Kriegman-Belhumeur Vision Technology (KBVT), Professor Peter Belhumeur and Professor David Kriegman, have been hired by Dropbox. Aditya Agrawal, VP of Engineering at Dropbox told Josh Constine of TechCrunch that Dropbox is in need of such expertise

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Data ScienceMachine Learning

Whenever someone needs to cite an example of the staggering volume of data generation today, Twitter is called upon. It’s no wonder this is the case- every single minute, 649 new users sign up to the service, and an astonishing 342,000 tweets are created. Handling this vast ocean of data-

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Machine LearningNews

Uber’s latest predictive model will deduce where you’re headed and it’ll be accurate 74% of the time. With the use of data analytics, the data team at Uber incorporated classic Bayesian statistics to set up a model that infers “where people ultimately want to go, rather than where people may

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ConversationsMachine Learning

In the first part of our interview with Sean Owen, Cloudera‘s Director of Data Science, we discussed the relationship between machine learning and Hadoop, the future of Apache Mahout and why machine learning has become such hot property. In this part of our discussion, we delved into the future of

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Machine LearningNews

Baidu is getting closer to finishing the world’s largest computer cluster for deep learning. The system is reported to have 100 billion digitally simulated neural connections conceived by heavy graphics processing units (GPUs). To put things in perspective the human brain has around a hundred trillion neural connections. Five years

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Data ScienceMachine LearningNews

Google’s Quantum Artificial Intelligence Lab, in partnership with scientists from several institutes in California, has launched its hardware initiative to design and build new quantum information processors based on superconducting electronics. An alliance between Google, NASA Ames Research Center and the Universities Space Research Association (USRA), the Quantum Artificial Intelligence

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