Source:- metrology.news Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes. Big data is a term applied to data sets whose size or type is beyond the ability of traditional relational Read More
Year: 2019
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Source:- dataconomy.com Why Understanding the Key Differences Between Data Science and Software Development Matters As Data Science becomes a critical value driver for organizations of all sizes, business leaders who depend on both Data Science and Software Development teams need to know how the two differ and how they should work together. Although there are lots Read More
Source:- towardsdatascience.com Pandas has become one of the most popular Data Science libraries out there. It’s easy to use, the documentation is fantastic, and it’s capabilities are powerful. Yet regardless of what library one uses, large datasets always present an extra challenge that needs to be handled with care. You start to run into hardware roadblocks Read More
Source:- kfgo.com ZURICH (Reuters) – As global currency markets grapple with a growing number of flash crashes triggered by shutdowns in algorithmic trading systems when volatility spikes, UBS is utilizing machine learning technology to carry on dealing. While algorithmic trading has played a growing role in the $5.1 trillion-a-day global foreign exchange market, accounting for up Read More
Source:- i-hls.com Big data is now the basis for any activity in the business, government, and security sectors. However, in many cases the information streamed to law enforcement agencies and security organizations is not synchronized with other databases and is not analyzed in an optimized way due to difficulties in coping with the amount of information and Read More
Source:- insidebigdata.com As data has transitioned from “nice to have” to a full-blown commodity, we’ve seen demand for data science and analytics (DSA) talent soar — along with opportunities for job-seekers and companies alike. This is such a critical moment for data science, in fact, that industries across the board are bracing for talent shortages. Here’s Read More
Source:- analyticsindiamag.com It is no surprise that data science today has become the backbone of several organisations across the globe. From the core to the edge, a lot of organisational decisions are based on data science. With time the job role of a data scientist is just becoming wider and talks about T-shaped data scientists is Read More
Source:- infoworld.com Machine learning uses algorithms to turn a data set into a predictive model. Which algorithm works best depends on the problem Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’d like to step back and explain both machine learning and deep learning in basic terms, Read More
Source:- designnews.com Machine learning is opening up new features and applications that will forever change how users expect their systems to behave. Machine learning for embedded systems has been gaining a lot of momentum over the past several years. For embedded developers, machine learning was something that data scientists were concerned with and something that lived Read More
Source:- themreport.com From online shopping to social media posts, the data trail consumers leave behind these days only grows longer and more telling. In fact, data scientists estimate that 90 percent of the world’s data was generated over the last two years alone, according to a 2018 article published by Forbes. What does this mean for Read More
Source:-cmswire.com In an ideal world, cybersecurity would take care of itself. But even with microservices, a contemporary architecture type with significant advantages over monolithic architectures, security remains an issue. In fact, some security issues are actually harder to resolve in a microservices architecture. While this topic is open to debate, CMSWire has spoken to industry experts Read More
Source: madison.com. Throughout the last century, we created and perfected the art of computer programming to automate mundane tasks. Conventional programs, however, still rely on hand-crafted rules, making programming a complicated and tedious task. Suppose you were to develop an email spam filter. Using traditional programming, you would have to read through millions of emails to Read More
Source: forbes.com. Data science and artificial intelligence are no longer buzz words in the biomedical research community. Physicians and other caregivers are increasingly being encouraged by hospitals and health insurance companies to utilize low-resolution dense biometric data captured using wearable medical devices. However classical healthcare heavily relies on high accuracy sparse datasets, i.e. patients are expected to get a thorough Read More
Source: healthcarefinancenews.com. As hospitals turn to technology to overhaul the patient experience and improve profits, a range of vendors from are bring new products and outsourced services to meet that demand with artificial intelligence, data analytics, and natural language processing as well as cognitive and process automation. Let’s take a look at the cutting edge technologies available Read More
Source:- forbes.com. Is the world too chaotic for any technology to control? Is technology revealing that things are even more chaotic and uncontrollable than first thought? Artificial intelligence, machine learning and related technologies may be underscoring a realization Albert Einstein had many decades ago: “The more I learn, the more I realize how much I don’t Read More
Source:- techiexpert.com. Machine learning enables computers to assist humans in analyzing data from giant, advanced information sets. one amongst the advanced information is biology and genomic information that has to analyze a varied set of functions mechanically by the computers. These machine learning strategies will offer additional help for creating this information for any usage like cistron Read More
Source:- datamation.com. By definition, Big Data is all about collecting large (or “Big”) volumes of structured and unstructured data. What makes Big Data useful is analysis of the collected information to find patterns and meaning that otherwise would be left undiscovered. Making sense of Big Data is the realm of Big Data analytics tools, which provide different capabilities for organization Read More
Source:- gartner.com. CIOs can make the most of artificial intelligence by applying it to strategic digital business objectives. Artificial intelligence (AI) can augment or automate decisions and tasks today performed by humans, making it indispensable for digital business transformation. With AI, organizations can reduce labor costs, generate new business models, and improve processes or customer service. However, most Read More
Source:- analyticsinsight.net. The term big data stands for an extremely voluminous set of data, which can expose connections, trends, and patterns in the behavior of the target group. In the education sector, data analysis can change the way the teacher teaches and the students learn. A single educational institution receives a great deal of information on a daily Read More
Source:- utilitydive.com. Smart technology puts intelligence where it’s needed We often associate artificial intelligence (AI) and machine learning (ML) with exotic applications – self-driving cars, speech and facial recognition, robotic control and medical diagnosis – all powered by massive rows of servers filled with CPUs or GPUs, at some distant data center. But in fact, AI Read More
Source:- adtmag.com. Google’s Android developer team updated ML Kit, which packages up the company’s machine learning expertise and technology for mobile developers creating Android or iOS apps. ML Kit provides base APIs ready to be used “out of the box” for tasks such as creating custom models used on-device or in the cloud. The kit is used Read More
Source:- activestate.com. These days, it seems like Machine Learning (ML) is everywhere. Well, everywhere except in legacy applications. But you can hardly blame the application if it was created prior to the recent advances in Python that have made ML mainstream (i.e. the last 3-5 years). Unfortunately, rewriting or refactoring legacy applications is typically a cost-prohibitive non-starter. Read More
Source:- irishtechnews.ie. The tech world is one of the spaces that experiences the fastest changes and developments. This is because, at its core, it needs change and optimization to survive and progress. In the end, it has become a dynamic and vibrant industry full of innovative solutions to problems. The internet has literally changed our lives Read More
Source:- forbes.com. Turns out after they’ve been trained on enormous datasets, algorithms can not only tell what a picture is such as knowing a cat is a cat but can also generate absolutely original images. The artificial intelligence that makes this possible has matured significantly in recent years and in some applications is very proficient, but Read More
Source:- npr.org When Merdis Wells visited the diabetes clinic at the University Medical Center in New Orleans about a year ago, a nurse practitioner checked her eyes to look for signs of diabetic retinopathy, the most common cause of blindness. At her next visit, in February of this year, artificial intelligence software made the call. The Read More
Source:- searchmicroservices.techtarget.com APIs help run the world. They allow software applications and digital platforms to interact with each other, orchestrating the exchange of requests between apps that have their own architectures. And, when properly managed, APIs ensure a neat, simplified experience for developers. The challenge is to be sure proper API management is entrenched in your Read More
Source:- smallbiztrends.com our business operates under a rock on an isolated island in the South Pacific. So you know artificial intelligence (AI) is the big thing today. AI assists consumers in their day-to-day activities with or without their knowledge. Consider services like voice assistance, online shopping, content streaming, and even texting. Machine learning (ML) is an application of Read More
Source:- ciodive.com Large, successful companies are increasingly embracing the value of the data science function and its potential to deliver powerful insights, better outcomes, and personalized customer experiences. Growth in the application of data science is evident in new hiring trends, increased spending in areas like technology and data science, as well as an overall cultural Read More
Source:- www.forbes.com The 21st century has brought many incredible new technologies that were once dreamed about in old sci-fi epics, and even some technologies we never saw coming. However, artificial intelligence — sometimes called machine intelligence or just AI — is proving to be one of the most disruptive of all. It’s already being applied by businesses across the Read More
Source- zdnet.com The enterprise has long since eclipsed the days of manually analyzing data, as doing so is both expensive and impractical considering the sheer amount of data organizations generate. For years, this task has been delegated to programmers, who often were tasked with creating custom scripts requiring frequent revision and fine-tuning. Those days are Read More