Source – forbes.com When businesses identify a problem that can be solved through machine learning, they brief the data scientists and analysts to create a predictive analytics solution. In many cases, the turnaround time for delivering a solution is pretty long. Even for experienced data scientists, evolving machine learning models that can accurately predict the results Read More
Tag: data scientists
Source – hbr.org Rise Science came to IDEO with a challenge. The young startup had built a robust data platform for college and professional athletes to track their sleep and adjust their behavior so that they played at peak performance. But for the players, the experience was challenging. Rise expected athletes to look at data-driven charts Read More
Source – informationweek.com It’s no secret that investing in data can lead to major benefits for organizations. Not only is data vital to success, companies that utilize insight-driven practices are twice as likely to be market leaders within their industries. When you combine that perspective with the fact that upward of 80% of all collected data goes unused, Read More
Source – techtarget.com If you were to visit some data scientist’s home at night and peek in the window, you might see a computer running with its screensaver disabled. That’s because the data scientist had to bring home analytics work that takes too long to run in the corporate data center. This story is shared in Read More
Source – jaxenter.com Data Science, Machine Learning, and Artificial Intelligence are attracting big money today. Many organizations, big and small, are investing millions in research — and people — to build powerful data-driven applications. Python and R have long been the two languages said to have a hold on the data science world, but that’s not Read More
Source – cio.com.au In IT, the bigger the hype, the greater the misconceptions, and data analytics is no exception. Analytics, one of the hottest facets of information technology today, can result in significant business gains, but misperceptions can get in the way of a smooth and timely delivery of analytical capabilities that might benefit business users Read More
Source – manitobacooperator.ca An expedition through published and unpublished studies on neonicotinoid pesticides has led a Guelph research team to find no colony-level risk to honeybees from the seed treatments — if they’re correctly used. The University of Guelph team, led by toxicologist Keith Solomon and adjunct professor Gladys Stephenson, analyzed 64 papers from “open, peer-reviewed Read More
Source – informationweek.com If you want build trust in machine learning, try treating it like a human, asking it the same type of questions. During the 2008 financial crisis, the banking industry realized that their machine learning algorithms were based on flawed assumptions. So financial system regulators decided that additional controls were needed, and regulatory Read More
Source – forbes.com Ranked No. 1 overall as the best job in America by Glassdoor, data scientists have quickly risen in prominence and critical importance within organizations. As technologies like the cloud, IoT and AI transform both the amount of intelligence companies can access as well as the speed at which they can innovate, a strong team of data scientists is no longer Read More
Source – insidebigdata.com Technologies such as smart sensors and the Internet of Things (IoT) are enabling vast amounts of detailed data to be collected from scientific instruments, manufacturing systems, connected cars, aircraft and other sources. With the proper tools and techniques, this data can be used to make rapid scientific discoveries and develop and incorporate more Read More
Source – dataconomy.com The importance of data science is only going to grow in the coming years. As we see the results of our data-empowered work take form in how we shape our businesses, our products and our own goals, we are beholden to take a reflective gaze at the relationship between our daily tasks and Read More
Source – itproportal.com It’s a key question for many data scientists – especially those that are new to the field: is Python or R better for data science? For those first venturing into the world of data science, it’s important to master one language first, rather than looking to be a Jack of all trades from Read More
Source – searchdatamanagement.techtarget.com NEW YORK — In the rush to capitalize on deployments of big data platforms, organizations shouldn’t neglect data quality measures that can ensure what’s used in analytics applications is clean and trustworthy, experienced IT managers said at the 2017 Strata Data Conference here last week. Several speakers pointed to data quality as Read More
Source – venturebeat.com Oracle added machine learning to its cloud management product to help better secure businesses against threats. The renamed Management and Security Cloud will take in data from on-premises and cloud infrastructure, then analyze them to help determine what might be a threat to a company’s data. When the system determines that something fishy is going Read More
Source – networkworld.com Nvidia and server makers Dell EMC, HPE, IBM and Supermicro announced enterprise servers featuring Nvidia’s Tesla V100 GPU. The question is, can servers designed for machine learning stem the erosion of enterprise server purchases as companies shift to PaaS, IaaS, and cloud services? The recent introduction of hardened industrial servers for IoT may indicate Read More
Source – techcrunch.com Microsoft, just like many of its competitors, has gone all in on machine learning. That emphasis is on full display at the company’s Ignite conference this where, where the company today announced a number of new tools for developers who want to build new A.I. models and users who simply want to make use of these Read More
Source – governmentcomputing.com Data Science Accelerator programme offers chance to experiment with different data science techniques and open source software A key data science joint initiative between the Office for National Statistics (ONS), the Government Digital Service (GDS) and the Government Office for Science and Civil Service analytical professions is approaching a closing date for applicants. The Data Read More
Source – formtek.com Deep Learning is quickly becoming a key component in the tool bag for Data Scientists. Deep Learning is a kind of Machine Learning that is being applied to applications like fraud detection, prodcut demand prediction, quality assurance, and predictive and prescriptive maintenance. Alexander Linden, research vice president at Gartner, said that “deep learning is Read More
Source – cio.com Machine learning (ML) is fast becoming a litmus test for forward-thinking CIOs. Companies that fail to adopt machine learning for product development or business operations risk falling behind more nimble competitors in the coming decade. That’s according to Dan Olley, who as the CTO of Elsevier, the scientific and health information unit of RELX Group, has ratcheted Read More
Source – indiatimes.com When you buy a product from an online marketplace, have you ever wondered how your order gets processed among millions of others? Does it baffle you how some banks use chatbots to solve customer queries based on transaction history, or that financial and portfolio management institutions deploy sentiment analysis and algorithms to consistently Read More
Source – datanami.com As the AI services ecosystem expands, vendors are offering automation tools designed to make life easier for embattled data scientists through toolkits used to build machine and deep learning models, and then move those trained models to production. That’s the premise behind the upgraded version of machine learning “lab” from toolkit vendor deepsense.ai Read More
Source – cio.com Until recently, data scientists could design algorithms with the assumption that the data to be explored would be brought together in a single, centralized repository, such as a data lake or a cloud data center. But with the explosion of data and the rise of the Internet of Things (IoT), social media, mobility and Read More
Source – eos.org The vast and rapidly increasing supply of new data in the Earth sciences creates many opportunities to gain scientific insights and to answer important questions. Data analysis has always been an integral component of research and education in the Earth sciences, but mainstream Earth scientists may not yet be fully aware of many Read More
Source – iamwire.com 2016 turned out to be a great year for Artificial Intelligence. It had all of our attention and no one seemed to be bothered. Many start-ups tried their luck with AI. Everyone started to talk about how Artificial Intelligence is going to change lives and how it’s the “big thing”. 2017 did not Read More
Source:- readitquik.com Data analytics is amongst the hottest emerging technologies in recent times, with applications ranging from marketing to customer service to HR and beyond. However, ever since its inception a few years back, even the nature of analytics has changed a lot. Today, the focus is a lot on predictive modelling and complex machine Read More
Source – infoworld.com Data scientists are in high demand, and this skills shortage looks to continue for the next few years. According to a study by IBM, by 2020 the number of annual job openings for all data savvy professionals in the United States will increase from 364,000 openings to 2,720,000. Furthermore, according to the study, the Read More
Source – computerweekly.com Well-established enterprises like retailers or manufacturing companies now have an abundance of data at their disposal. Unfortunately, merely possessing vast amounts of raw data does not lead directly to increased efficiency or the rapid development of new revenue streams. Instead, everyone must now figure out exactly how to make this data work for Read More
Source – forbes.com Many professionals use data and analytics skills to produce something of value, but only a few get media buzz. Career topics are the most popular of the articles I write. Many people write me with questions about careers in analytics, nearly all of them from people whose idea of an analytics career is Read More
Source – loyalty360.org Keeping pace with trends in any industry is an integral point for loyalty marketers. When it comes to loyalty program science, Loyalty360 talked to Eoin O’Sullivan, global director of analytics/bBI at Snipp, to find out the latest trends that loyalty marketers should be aware of and incorporate into their respective business strategies. Can you Read More