Source – venturebeat.com In the early days of machine learning, hiring good statisticians was the key challenge for AI projects. Now, machine learning has evolved from its early focus on statistics to more emphasis on computation. As the process of building algorithms has become simpler and the applications for AI technology have grown, human resources professionals Read More
Tag: Data scientist
Source – siliconrepublic.com If you want to be a data scientist, what do you need to know? We asked some of the top employers for advice. There is a massive data science talent gap across the world but it’s still considered an extremely exciting career to get into. Data scientist, in turn, is now being touted Read More
Source – economictimes.indiatimes.com The phenomenal growth of cloud-based offerings such as Platform as a service (PaaS), Infrastructure as a service (IaaS) and Software as a service (SaaS) has resulted into bigger competition in the market, with the new addition being Machine Learning as a Service (MLaaS). Machine Learning has emerged as one of the fastest evolving Read More
Source – cioreview.com Data has been continuously flowing more than ever in our contemporary era. By applying necessary analytical measures on the colossal amount of Big Data, small and large businesses can identify new opportunities and improve the customer experience alike. As the population and the technology grows, so will the quantity of data increase. However, Read More
Source – insidebigdata.com In this special guest feature, Matthew Mahowald, Lead Data Scientist and Software Engineer for Open Data Group, shares his perspectives on how the speed at which tech and tools have been developed, has caused problems with the way analytic deployment is made possible. Matthew holds a Ph.D. in Mathematics from Northwestern University, with a Read More
Source – forbes.com The rapture of the machines. The subject of fiery debates and endless banter. Everyone is talking about how robots are going to get all our jobs and take over the entire world as soon as they get brains of their own. But that’s not how the real world is supposed to work. In Read More
Source – hbr.org Artificial intelligence is no longer just a niche subfield of computer science. Tech giants have been using AI for years: Machine learning algorithms power Amazon product recommendations, Google Maps, and the content that Facebook, Instagram, and Twitter display in social media feeds. But William Gibson’s adage applies well to AI adoption: The future Read More
Source – telegraph.co.uk Microsoft is setting up a new healthcare department at its Cambridge research facility, as part of plans to use its artificial intelligence software to enter the health market. The computer giant has created the division as part of its commitment to “transform healthcare” using technologies such as machine learning and cloud computing. Its Read More
Source – informationweek.com Three industry leaders took the stage at SAS Analytics Experience and provided broad perspectives on how far we’ve come in analytics over the last 10 years and where we are today. A decade ago the iPhone was a new device and there wasn’t an app for much of anything. Competing on analytics was Read More
Source – arstechnica.com Machine learning (ML) based data analytics is rewriting the rules for how enterprises handle data. Research into machine learning and analytics is already yielding success in turning vast amounts of data—shaped with the help of data scientists—into analytical rules that can spot things that would escape human analysis in the past—whether it be Read More
Source – siliconrepublic.com If you want to be a data scientist, the tech world is still rife with opportunities. As with most booming tech sectors, attracting enough talent to fill the demand is important. One way of doing this is to give visibility to the talent that is already there, highlighting the importance of data science Read More
Source – cbronline.com It’s safe to say that Python is a pretty popular tool across a whole range of industries and professions, thanks, no doubt, to the programming language’s accessibility, wealth of libraries and frameworks, and of course, its huge community of die-hard devs that claim Python should be the tool of choice for any self-respecting Read More
Source – insidebigdata.com As Big Data moves from hype to reality, more companies are adopting a “data first” approach. Data is used to formulate strategies, design products, embed intelligence in applications, and ultimately provide an awesome customer experience. With increased data awareness, executives are also demanding more from their data teams – just mining data to Read More
Source – betanews.com In my series, I’ve looked at the different ways in which data can be deployed to help people make decisions. Over time, more of the decision-making process has shifted from people manually collating data from different sources in their heads to using data sets that can be automatically joined together. This networked approach Read More
Source – techrepublic.com Career opportunities in the IT industry are booming in this era of technological advancement and information development. If you were considering jumping into the industry as a data specialist, there is no better time than now. Plus, you can easily get up to speed on the fundamental programs of the trade with The Big Read More
Source – eyefortravel.com/mobile-and-technology As head of data science at Trainline, Fergus Weldon, who will be speaking at EyeforTravel’s Smart Travel Data Summit 2017, is at the coalface of innovation. In an exclusive interview he shares ten things he knows about data science today. 1. Being a data scientist is being the voice of the customer In the past Read More
Source – martechadvisor.com If you search “Marketing and AI”, Google returns almost four million results. Recent headlines range from the strategic – AI Will Make Marketing Less Manual (well, duh) – to the tactical, like 4 ways AI can improve email marketing. The hype machine is in full swing. But here’s the rub: the vast majority of the conversations Read More
Source – datanami.com If you were a data scientist three years ago, you could pretty much write your own ticket. Everybody in the industry, it seemed, either wanted to hire a data scientist, or wanted to be one. But today, thanks to a confluence of factors, organizations are beginning to question whether they need these digital Read More
Source – information-management.com Reports to: Depending on the organizational structure of the business in which you as a data scientist find yourself in, you may be reporting into a lead data scientist, a principal, a chief technology officer, a chief data officer or in cases of some start up organizations, perhaps a CEO. As with your responsibilities, Read More