Source:-analyticsindiamag.com Big data analysts need the right tools which empower them to analyse and make robust decisions in an organisation. In this article, Analytics India Magazine lists down 15 top analytical tools that all persons who work with Big Data must use in 2019: 1| Apache Spark Apache Spark is a fast and general-purpose cluster computing system which provides Read More
Source:- via.news Artificial intelligence, machine learning, and deep learning are arguably the most significant innovations taking the 21stcentury by storm. Differentiating between the three terminologies is no easy feat, which explains why they are often used interchangeably. What is Artificial Intelligence? Artificial intelligence is the art of trying to integrate human intelligence into machines. Put, it Read More
Source:- ecns.cn President’s message calls for tackling legal, security, governance challenges President Xi Jinping called on Sunday for strengthened cooperation among countries to explore opportunities of digital, internet-based intelligent development and to properly address legal, security and governance challenges arising from big data industry development. He made the remarks in a congratulatory letter to the China Read More
Source:- builtin.com At their core, data scientists have a math and statistics background. Out of this math background, they’re creating advanced analytics. On the extreme end of this applied math, they’re creating machine learning models and artificial intelligence. Just like their software engineering counterparts, data scientists will have to interact with the business side. This includes Read More
Source:- uctoday.com Data is everywhere, but are we using It correctly? Big data is an ever-evolving and dynamic term that describes large volumes of data with the potential to deliver useful insights and information. Big data can inform machine learning strategies, form the basis of artificial intelligence applications, and transform business operations. For years, Big Data was defined by Read More
Source:- thedailybeast.com Online data plays an almost inextricable role in American consumers’ lives. Following a host of large-scale data breaches and subsequent questions about corporations’ use of consumer data, Capitol Hill has been abuzz with talk of creating federal data privacy legislation. Amidst calls for federal data privacy protection laws, many industries that handle sensitive consumer Read More
Source:- ibtimes.com Measles, once thought to have been eliminated in the U.S., is popping up in isolated outbreaks as a result of skipped well-child visits and parents’ fears that the measles-mumps-rubella (MMR) vaccine is linked to autism. Though some 350 measles cases occurred in 15 states in the first three months of 2019, more than half Read More
Source:- themandarin.com.au Data science is increasingly important across both Federal and State Government sectors, especially with the implementation of machine learning. Machine learning is helping these sectors organise, program and analyse data, by automating processes and freeing up human resources that can be better applied in other areas. A more specific subset of artificial intelligence (AI), Read More
Source:- forbes.com Recently San Francisco passed – in an 8-to-1 vote — a ban on local agencies to use facial recognition technologies. The move is likely not to be a one-off either. Other local governments are exploring similar prohibitions, so as to deal with the potential Orwellian risks that the technology may harm people’s privacy. “In Read More
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
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