Artificial intelligence (AI), deep learning, and neural networks represent incredibly exciting and powerful machine learning-based techniques used to solve many real-world problems. For a primer on machine learning, you may want to read this five-part series that I wrote. While human-like deductive reasoning, inference, and decision-making by a computer is still a long time away, there have been remarkable gains in the application of AI techniques and associated algorithms. The concepts discussed here are extremely technical, complex, and based on mathematics, statistics, probability theory, physics, signal processing, machine learning, computer science, psychology, linguistics, and neuroscience. That said, this article is not meant to provide such a technical treatment, but rather to explain these concepts at a level that can be understood by most non-practitioners, and can also serve as a reference or review for technical folks as well.

The advancement could mark a major breakthrough in the development of AI, as the "differentiable neural computer" (DNC) can solve problems without any prior knowledge. Instead, the DNC learns to use its own memory to answer questions about complex data. In a study published in the journal Nature, the technology also demonstrated it can solve a block puzzle game using reinforcement learning. What makes the DNC impressive is that it can learn to form and navigate complex data structures all on its own. The researchers demonstrated how the program can analyze a description of an arbitrary graph and answer questions about it.

If you have and you want to learn the science behind them, you have come to the right place. In this course, I will show you how these companies use Recommender systems or Machine Learning to influence your purchasing decisions. This course is timely and extremely relevant now as almost all major service-oriented companies function on recommender systems. You will understand how these systems work and learn how to build and use your own recommender systems, just like these big companies do. Learn how to build the recommender systems that are being used by almost every big service-oriented company in today's world with this introductory course for beginners.

The ability to apply machine learning techniques to large datasets is becoming a highly sought-after skill in the world of technology. Scala can help you deliver key insights into your data--its unique capabilities as a language let you build sophisticated algorithms and statistical models. For this reason, machine learning and Scala fit together perfectly and knowledge of both would be beneficial for anyone entering the data science field. The course starts with a general introduction to the Scala programming language. From there, you'll be introduced to several practical machine learning algorithms from the areas of exploratory data analysis.

In 2014, IBM launched the Watson Developer Cloud, making the power of cognitive computing available to developers across the world through a set of APIs on IBM's BlueMix platform. We've seen volumes of applications built by companies covering everything from personal health and fitness to travel and entertainment to financial services. It was amazing to see these early adopters jump onboard and showcase the power of cognitive computing. We want to make it even easier for developers to learn how to build and deploy cognitive applications – and even more importantly, to distinguish themselves for having developed these critical skills. That's why today, IBM is announcing a new program -- the IBM Watson Application Developer Certification -- designed to help developers all across the world build and validate their skills as well as connect with companies looking to leverage their unique talents. We watch every day as individuals explore and apply Watson in new ways -- from building natural language interfaces in a variety of languages so consumers can get answers faster to helping doctors uncover critical new insights from medical imagery.

Samsung, announced that it has agreed to acquire Viv Labs, the intelligent interface to everything. Viv has developed a unique, open artificial intelligence (AI) platform that gives third-party developers the power to use and build conversational assistants and integrate a natural language-based interface into renowned applications and services. The transaction is subject to customary closing conditions. The deal showcases Samsung's commitment to virtual personal assistants and is part of the company's broader vision to deliver an AI-based open ecosystem across all of its devices and services. With Viv, Samsung will be able to unlock and offer new service experiences for its customers, including one that simplifies user interfaces, understands the context of the user and offers the user the most appropriate and convenient suggestions and recommendations.

Scientists at Google have created an artificial intelligence program that can compute problems requiring strategic reasoning, The Guardian reports. The algorithm, part of an emerging field called deep learning, is able to master tasks independently using external memory, similar to the way humans work through a new recipe, according to the study published in Nature. In this case, it was able to figure out on its own the quickest route between stops on the London Underground and reassess if the destination was overshot. This could pave the way to more efficient virtual assistant applications, which might be bad news for Apple's sassy sidekick.

Using software to compare genetic information in bacterial isolates from animals and people, researchers have predicted that less than 10% of Escherichia coli 0157:H7 strains are likely to have the potential to cause human disease. According to Nadejda Lupolova, from the University of Edinburgh, Scotland, and colleagues, "machine-learning approaches have tremendous potential to interrogate complex genome information for which specific attributes of the organism, such as disease or isolation host, are known." The researchers published the results of their study in Proceedings of the National Academy of Sciences. Although most E. coli strains live in the gastrointestinal tracts of people and animals without causing disease, infection with E. coli 0157 is associated with serious illness in people. E. coli 0157 was first identified as a cause of disease in the United States in 1982, during an investigation into an outbreak of hemorrhagic colitis.

While many advances have been made, it still has been difficult for non-programmers to create objects made of many materials (or mixtures of materials) without a more user-friendly interface. But this week, a team from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) will present "Foundry," a system for custom-designing a variety of 3-D printed objects with multiple materials. "In traditional manufacturing, objects made of different materials are manufactured via separate processes and then assembled with an adhesive or another binding process," says PhD student Kiril Vidim?e, who is first author on the paper. "Even existing multi-material 3-D printers have a similar workflow: parts are designed in traditional CAD [computer-aided-design] systems one at a time and then the print software allows the user to assign a single material to each part." In contrast, Foundry allows users to vary the material properties at a very fine resolution that hasn't been possible before.

We propose a novel stacked generalization (stacking) method as a dynamic ensemble technique using a pool of heterogeneous classifiers for node label classification on networks. The proposed method assigns component models a set of functional coefficients, which can vary smoothly with certain topological features of a node. Compared to the traditional stacking model, the proposed method can dynamically adjust the weights of individual models as we move across the graph and provide a more versatile and significantly more accurate stacking model for label prediction on a network. We demonstrate the benefits of the proposed model using both a simulation study and real data analysis.