Parq!

Data science and machine learning have emerged as the keys to unlocking value in enterprise data assets. Unlike traditional business analytics, which focus on known values and past performance, data science aims to identify hidden patterns in order to drive new innovations. Behind these efforts are  the programming languages used by data science teams to clean up and prepare data, write and test algorithms, build statistical models, and  translate into consumable applications or visualizations. In this regard, Python stands out as the language best suited for all areas of the data science  and machine learning framework. In a recent white paper “ Management’s Guide – Unlocking the Power of Data Science & Machine Learning with Python ,” ActiveState – the Open Source Language Company – provides a summary of Python’s attributes in a number of important areas, as well as considerations for implementing Python to  drive new insights and innovation from big data. ...

Scality , a leader in object and cloud storage, announced the open source launch of its Scality Zenko, a Multi-Cloud Data Controller. The new solution is free to use and embed into developer applications, opening a new world of multi-cloud storage for developers. Zenko provides a unified interface based on a proven implementation of the Amazon S3 API across clouds. This allows any cloud to be addressed with the same API and access layer, while storing information in their respective native format. For example, any Amazon S3-compliant application can now support Azure Blob Storage without any application modification. Scality’s vision for Zenko is to add data management controls to protect vital business assets, and metadata search to quickly subset large datasets based on simple business descriptors. We believe that everyone should be in control of their data,” said Giorgio Regni, CTO at Scality. “Our vision for Zenko is simple—bring control and freedom to the developer to unleash...

There are few things social media users love more than flooding their feeds with photos of food. Yet we seldom use these images for much more than a quick scroll on our cellphones. Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) believe that analyzing photos like these could help us learn recipes and better understand people’s eating habits. In a new paper the team trained an AI system to look at images of food and be able to predict the ingredients and suggest similar recipes. In experiments the system retrieved the correct recipe 65 percent of the time. In computer vision, food is mostly neglected because we don’t have the large-scale data sets needed to make predictions,” says Yusuf Aytar, a postdoctoral associate who co-wrote a paper about the system with MIT professor Antonio Torralba. “But seemingly useless photos on social media can actually provide valuable insight into health habits and dietary preferences.” The paper will be prese...

In this special guest feature, Srikant Menon, Practice Director of Internet of Things (IoT) at Happiest Minds Technologies, discusses how it is imperative for businesses to balance the massive benefits of IoT along with the security risks it poses. While millions of “things” are simple in nature, IoT security is an absolute must and should require an end-to-end approach. via insideBIGDATA http://ift.tt/2w0ljpN

Here is a question I was asked to discuss at a conference last month: what is Artifical Intelligence (AI)?  Instead of trying to answer it, which could take days, I decided to focus on how AI has been defined over the years.  Nowadays, most people probably equate AI with deep learning.  This has not always been the case as we shall see. Most people say that AI was first defined as a research field in a 1956 workshop at Dartmouth College.  Reality is that is has been defined 6 years earlier by Alan Turing in 1950.  Let me cite Wikipedia  here: The Turing test , developed by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation is a machin...

Compared to other sectors, like finance and technology, retail can be considered a late adopter of the advantages offered by business intelligence to daily processes. This is a paradox, as the operations in retail are some of the most well adjusted for the insight provided by digital dashboards. Questions like: “Who is your ideal client?”, “What are the products you should promote?” and “Which items should you sell as a bundle?”, “What is the preferred way of paying?” and “How do your clients engage with your brand?”, can all be answered through a BI platform that integrates point of sale data with demographics and interactions from online interfaces. Why is Business Intelligence a solution for retail? The value of BI comes from the evolution of retail companies from organizations based on operations to companies built on innovation. The intermediate stages are consolidation, integration, and optimization. This is a journey from ad-hoc to automation, from naïve to well-defined proc...

We all like to feel as if we have an intuitive sense of what our businesses need to succeed, but the reality is that successful companies rely on big data analytics to continuously understand, measure and improve. With powerful computing available via the cloud, and more tools and services for data collection and analysis than ever before, you can gain the edge over your competition, streamline your operations, connect with the right customers and even develop or refine the right products, using the unprecedented insights from big data. Refine your business strategy by integrating big data analytics into these five business areas: Process improvement – work smarter This is often one of the first areas businesses target and think of when it comes to big data analytics. Collecting data on your business process or production invariably exposes inefficiencies and opportunities. While there are often financial gains, resource use or reuse, scheduling and fulfillment/delivery are all are...

The Silicon Valley reverberates of Machine Learning today as Artificial Intelligence (AI) continues to reshape, mold and revolutionize the world. Machine learning is a fragment of AI and a very significant one. It is a subset of AI that has proved to be successful for technology to make headway. Artificial intelligence is based on Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering. It is the exploitation of computer functions that are related to human intelligence, such as reasoning, learning and problem-solving. Where Artificial Intelligence aims to build machines that are capable of intelligent behavior Machine Learning is its application getting computers to work without being unequivocally programmed. It is based on algorithms that need not rely on rules-based programming. Machine learning makes it easier to develop smart and sophisticated software that decreases human effort and saves time. Years of work can be made a matter of minutes and seconds...

The ubiquitous influence of Artificial Intelligence and Machine Learning is inescapable. The two terms although virtual and are mostly used interchangeably, are entirely different. Before I dig into the complexities of the two, the best way to give an outline of the two would be to say; Artificial Intelligence bodies the whole concept of machines being able to act intelligently and smartly. Whereas, Machine learning is an approach of Artificial Intelligence or a figment which emphasizes on providing data to the computers which it will analyze and then come up with the best possible solution on its own. THE JOURNEY OF PROGRESS The research labs have long been simmering with Artificial Intelligence, and it has been in use for a very long time. For decades now, as the mind has progressed and our understanding has improved, new locks to Artificial Intelligence have been opened, and there is yet more to achieve. Machine learning stems from the minds of early AI crowd. Artificial Intelli...

The wave of Machine Learning has hit and transformed every sector, affecting the way we take our decisions. The widespread use of Big Data among all the industries has sparked the use of machines to detect patterns and previse future. With multiple complicated territories which Machine Learning has been able to conquer such as data mining, natural language processing (NLP), image recognition, and expert systems, it is said to be the foundation of future civilization. Machine Learning is a very promising approach of Artificial Intelligence, one which is radically reshaping the present and the future!   MACHINE LEARNING AND ITS WORKING Machine learning is actually a bottomless pit. It encompasses a lot of things. The assumption laying the ground for Machine Learning is the analytical solutions that are reached by studying previous data models. It is the process whereby Artificial Intelligence is developed in computers to make them work without being programmed and as efficientl...

Big data is transforming the way businesses conduct operations. Data is gathered in many ways through online searches, analysis of consumer buying behavior and more, and companies use this data to improve their profit margin and provide an overall better experience to customers. While big data is used in many industries around the globe, the travel industry stands to gain a tremendous amount from its use. Many larger companies are already using big data creatively, but you may not understand the true value it can provide for your business. With a closer look at how big data is transforming the travel industry , you can better determine how your own business can benefit from its use. Greater Personalization The travel industry includes a wide range of businesses, such as rental car companies, hotels, airlines, tour operators, cruise lines and more. Each of these companies must find a way to improve the overall customer experience and to meet the unique needs of each customer, and bi...

Neural networks, which learn to perform computational tasks by analyzing large sets of training data, are responsible for today’s best-performing artificial intelligence systems, from speech recognition systems, to automatic translators, to self-driving cars. But neural nets are black boxes. Once they’ve been trained, even their designers rarely have any idea what they’re doing — what data elements they’re processing and how. Two years ago, a team of computer-vision researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) described a method for peering into the black box of a neural net trained to identify visual scenes. The method provided some interesting insights, but it required data to be sent to human reviewers recruited through Amazon’s Mechanical Turk crowdsourcing service. At this year’s Computer Vision and Pattern Recognition conference, CSAIL researchers will present a fully automated version of the same system. Where the previous paper re...

Novosibirsk State University is one of the major research and educational centers in Russia and one of the largest universities in Siberia. When researchers at the University were looking to develop and optimize a software tool for numerical simulation of magnetohydrodynamics (MHD) problems with hydrogen ionization —part of an astrophysical objects simulation (AstroPhi) project—they needed to optimize the tool’s performance on Intel® Xeon Phi™ processor-based hardware. via insideBIGDATA http://ift.tt/2uapUHU

I attended the interview with Nick Drake, Senior Vice President, Direct to Consumer at T-Mobile and Otto Rosenberger who serves as CMO at the Hostelworld Group at the Adobe Summit. The key take away of the entire session was that customer experience is the beginning and the core of digital transformations – it is where it all begins. T-Mobile and Hostelworld are completely different companies, but what kind of connects them is the fact that they both focused on customer experience when transforming their companies. So why is customer experience the key to it all? Because it links organizations to customers at an emotional and physiological level. The story of Hostelworld Hostelworld is now a leading hostel booking platform. Three years ago, it was set up as just a booking engine, as a transactional business. Today, the company accompanies their customers throughout the entire trip. Hostelworld operates globally, with most of the customers based in North America, whereas 30% to 35%...

Digital Transformation has brought in all the new concepts and technologies at the hands of consumers and businesses alike. Digital Twin is one of them. It is a virtual image of your machine or... ... via Planet big data http://ift.tt/2s5q6Zz

For years, the necessity to acquire large amounts of digital data has surpassed the somewhat blatant disorganization of said gathered data. These massive compilations of data, coined “big data,” may be the key to business strategy, improvement, and pattern analysis. However, big data is all too often gathered inconsistently and can often be difficult to display to the user in an effective manner. Although there have been multiple improvements to both the collection and visualization of big data in the last few years alone, including the implementation of 3-D spatiotemporal interactive data visualization software , some believe this data visualization can even go one step further and delve into the vast world of virtual and augmented reality. However, others believe that this format could prove to be even more difficult than the basic big data visualizations of today and would ultimately be a step in the wrong direction when it comes to improving the way we currently look at big data....

I attended the  Huawei European Innovation Day  recently, and was enthralled by how the new technology is giving rise to industrial revolutions. These revolutions are what will eventually unlock the development potential around the world. It is important to leverage the emerging technologies, since they are the resources which will lead us to innovation and progress. Huawei is innovative in its partnerships and collaboration to define the future, and the event was a huge success. For many people, the concept of  Artificial Intelligence (AI)  is a thing of the future. It is the technology that has yet to be introduced. But  Professor Jon Oberlander  disagrees. He was quick to point out that AI is not in the future, it is now in the making. He began by mentioning Alexa, Amazon’s star product. It’s an artificial intelligent personal assistant, which was made popular by Amazon Echo devices. With a plethora of functions, Alexa quickly gained much popularity an...