Machine Learning Tools You Should Know About

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Machine Learning Tools You Should Know About

Artificial intelligence, big data, and hybrid cloud computing have made a significant impact on the business industry. Joining this list is machine learning. This new advancement in business technology provides machines with the ability to learn data and store information without being specifically programed to do so. Machine learning tends to focus on developing computer programs that are able to make the necessary adjustments when new data presents itself.

Every new development in the technological industry is followed by new tools. These tools work to help businesses and users stay up to date with all the technological advancements. Some specific tools that will help businesses as they incorporate and work with machine learning are Amazon Machine Learning, Tensor Flow, Azure Machine Learning Studio, H20, Caffe, MLlib, and Torch.

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Busting the 7 Biggest Employer Branding Myths of All Time.

Based on Google Trends data and anecdotal evidence in the form of podcast topics in the HR, this is the year of Employer Brand (at least in the talent acquisition community).

I say this like people who say this is the year of women in Hollywood or the year of mobile in tech, that is with tongue firmly in cheek, knowing full-well that employer brand has always been important, whether we listen to expert-stocked panels at conferences.

But ask ten people what an employer brand is and where it comes from and you’ll get ten answers, which is no way to facilitate growth.

So by way to establishing a definition and getting everyone on the same page, here are the seven most common myths about employer brand…busted.

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How Anaconda’s data science platform will help IBM speed up enterprise machine learning adoption

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How Anaconda’s data science platform will help IBM speed up enterprise machine learning adoption

IBM announced that it will offer open data science platform Anaconda on IBM Cognitive Systems. Here’s how it could help your business.

On Monday, IBM announced that it has partnered with Continuum Analytics to offer open data science platform Anaconda on IBM Cognitive Systems. Anaconda, which is powered by Python, will also integrate with IBM’s PowerAI software for machine learning and deep learning, making it easier and faster for businesses to analyze and gain insights from data-intensive cognitive workloads.

“Anaconda is an important capability for developers building cognitive solutions, and now it’s available on IBM’s high performance deep learning platform,” said Bob Picciano, senior vice president of Cognitive Systems, in a press release. “Anaconda on IBM Cognitive Systems empowers developers and data scientists to build and deploy deep learning applications that are ready to scale.”

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Software Engineering Has Become Way More than Coding

Software engineering firm Cambridge Consultants notes that among their hundreds of engineers, most are involved in design. Few actually do coding.

In spite of common misperceptions, software engineers are not strapped to workstations slaving over code. Code may have been a central facet of software activity in past years, but that is changing as companies incorporate more software into their products to improve and differentiate them. Software engineers are moving from coding to design and from design to management.

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‘The engine of change’: SAS Institute says it wants to bring its analytics everywhere

At the company’s annual user conference in Orlando, Dr. Jim Goodnight, CEO of analytics giant SAS Institute, told the over 5,600 users in attendance and more than 30,000 joining via live stream that SAS is on a mission to bring analytics everywhere.

“And if analytics is the engine of change, data is the fuel,” he said. “The opportunity is enormous.”

The company’s growth illustrates that. When Goodnight co-founded the SAS Institute in 1976, analytics was a niche technology. That first year the company made US$138,000. But along with the explosion of data came the need to do something with it, and analytics finally took off. In 2016, SAS made US$3.2 billion, had over 83,000 customers and over 14,000 employees (almost 350 in Canada).

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The Future Of Social: Crowd-Sourcing And Artificial Intelligence

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The Future Of Social: Crowd-Sourcing And Artificial Intelligence

In 2005, 5% of adults in the U.S. were on social media; today it’s around 70%. Facebook has over 1.65 billion users engaging for more than 50 minutes per day. Social media is ubiquitous, and smart brands are sprinting to keep pace. But what about getting ahead of the curve?

What has evolved beyond Social Monitoring to Social Listening is now poised to enter a 3.0 phase in which crowd-sourcing and artificial intelligence will play pivotal roles.

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How Colleges Use Big Data to Target the Students They Want

By tracking prospective pupils’ digital footprints, schools can make calculated decisions about their admissions outreach—for a price.

A decade ago, Saint Louis University found itself in a precarious situation. About half of the university’s 8,600 undergraduates were from Missouri and Illinois, and the demographic forecast for the Midwest looked bleak: the number of high-school graduates from the region was projected to drop by nearly a third by 2028.

So the university started to dig deeper for prospects in its backyard, purchasing more names of prospective high-school students from the College Board and ACT and targeting those teenagers with marketing materials. At one point, admissions officials at Saint Louis University were buying upwards of 250,000 names annually.

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On Topic: Tech news to know now

Here’s what’s going on in tech…

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Data Science Through the Ages

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Data Science Through the Ages

What if personal attitudes could predict trends in the United States economy? On Wednesday, Dr. James Lepkowski of the University of Michigan visited Kalamazoo College to discuss one area of his research: how regular people can predict vast economic trends simply by participating in a basic questionnaire, as proven through decades of surveys.

“So what do individual consumers and their attitudes have to do with how the economy is going to behave?” The data scientist specifically discussed a survey that began in 1946 called “Measuring Individual Attitudes about the Economy” and aimed “to measure the attitudes for personal and national economic attributes.” The personal attributes, he explained, ask basic questions regarding individual finance: ‘Do you think your finances are going to get better, worse, or stay about the same? In the next month? In the next 12 months?’ The national attributes consist of similar but larger-scale questions: ‘Do you think that the business condition in the next 12 months are going to get better, worse, or stay about the same?’ “The questions are that basic.”

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6 Signs of Dirty Data [Infographic]

Less risqué than Dirty Dancing, less provocative than Dirty Diana—dirty data is something you want to keep away from your company. You know from the name that’s it’s probably not good, but what is dirty data?

Simply put, it’s data that has errors, mistakes, and is incomplete in some way. And it’s costing you and your company money. Chances are you, or at least someone at your company knows that’s a problem, but more than 90 percent of companies still aren’t keeping their data clean.

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DataScience Launches Interactive Tool For Exploring Data Science Trends

DataScience, Inc., today announced a new interactive tool for exploring and visualizing trends in data from more than 2.8 million GitHub repositories. With DataScience Trends, users can easily compare activity across the open source libraries now replacing legacy solutions in enterprise data science, from deep learning to distributed processing, all without writing code.

The tool allows non-technical audiences to visually compare more than 20 events, from new commits to pull requests, across the three terabytes of data released publicly by GitHub and Google last year. DataScience Trends’ easy-to-use interface also makes it simple to mine GitHub for information and interact with trends on a timeline, all within a customizable date range.

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Content Marketing Statistics And Trends – 2017 Edition

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Content Marketing Statistics And Trends – 2017 Edition

In an online world of marketing, where there’s a new viral trend every day and a new set of „you must try this“ type of advice every week, one thing is constant for years, and that is the importance of good, quality content.

It is the same for any kind of internet marketing: whether you are a B2B or B2C marketer, you need good content to attract people to your website and, eventually, have them spend some money.

Research has shown – over 2/3 of customers feel better about a brand after they consume some kind of content from them. So it comes as no surprise that many companies are decreasing their budget for „traditional“ marketing and investing more in digital campaigns.

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The Art of Conversation: avoiding short-termism

Ever taken a short cut? Even though you know it’s a quick fix and that you’re probably storing up problems for further down the line? Yeah, you know what I’m talking about.

Like that time when you super-glued the kitchen table back together, instead of getting out your toolbox. Or when you bought cheap trousers the day before your holiday, knowing they would likely split before the week was out.

It’s the same at work.

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The Data Pipeline – Analytics at the Speed of Business

Business leaders are growing weary of making further investments in business intelligence (BI) and big data analytics. Beyond the challenging technical components of data-driven projects, BI and analytics services have yet to live up to the hype.

Early adopters and proponents were quick to frame solutions as miraculous reservoirs of insight and functionality. However, big data has not met many C-level executives’ expectations. This disconnect has many executives delaying projects, filing end-to-end big data solutions under “perhaps, in the future.”

Increasing interest and investment in distributed computing, AI, machine learning and IoT are generating practical and user-friendly tools for ingesting, storing, processing, analyzing and visualizing data. Still, the necessary IT, data-science and development operations are time-consuming and often entail large resource displacements.

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Some of the Worst Digital Marketing Blunders of Recent Times and How to Fix Them

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Some of the Worst Digital Marketing Blunders of Recent Times and How to Fix Them

If you are involved in a business’s digital marketing efforts, the fear of a massive and very public blunder can easily cause you to wake in a cold sweat at the dead of night. Social media gaffes occur often, and while some brands embrace the publicity (negative though it may be), others suffer real reputational damage.

Here are just a handful of the worst digital marketing gaffes that have occurred recently and crucially – some tips on how you can avoid making the same mistakes…
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Google’s Fact Check Labeling System Goes Global

Google on Friday announced the extension of the Fact Check feature it introduced last fall in partnership with Jigsaw. Publishers now can display a Fact Check tag in news stories everywhere that Google News is available.

The company also has introduced the Fact Check feature globally in Google Search, in all of the languages it supports.

“For the first time, when you conduct a search on Google that returns an authoritative result containing fact checks for one or more public claims, you will see that information clearly on the search results page,” noted Jigsaw Product Manager Justin Kosslyn and Research Scientist Cong Yu in an online post.

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Web Dev To Data Scientist With Python

Python is currently very popular as a beginner’s programming language and has become the preferred language for introductory computer science courses. It is also a very versatile language, cropping up in many areas of expertise. Does this mean you can use it to switch career paths?

That’s the idea explored in the following infographic from DataCamp which sets out to consider how Pythonistas might be able to switch from web developer to data scientist – or vice versa.

Data Scientist continues to be a very popular career aspiration and it is easy to understand why. It ranks top of the 50 Best Jobs in America for 2017 and is amongst the top paying developer-related jobs worldwide according to the recent Stack Overflow survey.

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How introverts can nail a job interview

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How introverts can nail a job interview

Chutes and ladders of interviewing

Job interviewing can be a difficult process. There are many hoops to jump through and questions to answer; it can be hard to really let your best self shine when your mind is fixated on so many things.

This process can be even tougher for introverts. Introverts have a tendency to overthink and under-express, making interviewing a tricky business.

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Right data mining data sets are a must for proper predictive modeling

Predictive analytics applications can go off track quickly if data scientists and other analysts don’t make good choices on the data sets they’re looking to mine and analyze.

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Artificial Intelligence: Yes, machines are going to steal your jobs

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Artificial Intelligence: Yes, machines are going to steal your jobs

The World Economic Forum expects automation and Artificial Intelligence (AI), to result in the loss of at least 5 million jobs globally by 2020. Yes, machines are going to steal your jobs. It may sound like a scene from Terminator in which a robot may push you out of your office chair, but the reality is scarier and invisible to an extent. The major threat to your job is from machine learning.

Machine Learning is the ability to process huge volumes of data and complete tasks in a more efficient way than a human being can. We’re on the verge of a revolution in the modern workforce, and things are about to look very different.

White-collar jobs aren’t safe – Machines have replaced manual jobs but now machines can also think and learn and do the same tasks that a highly skilled worker can.

Here are some jobs already being replaced by AI, previously thought to be irreplaceable:

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Indeed says there’s a cybersecurity skills gap, could you capitalize on it?

Data breaches, election hacking, and remote spying are all very real issues we face, and surprise, apparently we’re not entirely equipped to deal with it. According to Indeed, there’s a huge global cybersecurity skills gap.

Indeed compiled two years of data from ten countries to identify where the greatest demand for cybersecurity jobs are and where the field is showing growth.

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When companies don’t treat their job applicants well, they lose out in more ways than one

When a company ignores your resume submission, fails to notify you of your application status or completely neglects you after a series of interviews, you never want to apply for a job there again. Last year, my firm worked with Career Arc to survey job seekers and found that 80% would be discouraged to consider other relevant job openings after a poor experience. Employers who fail to create a positive experience disregard professionals who could be in high demand in the future. Instead, they should look at the lifetime value of a candidate, much like they already do for customers.

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5 Market Research Tips Every Startup Should Know

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5 Market Research Tips Every Startup Should Know

Market research is imperative to the success of any business.

According to studies, some of the top reasons why startups fail include the lack of planning, the absence of supplier knowledge, and issues with pricing. Regardless of your niche, the chances of these occurring can be greatly reduced, if not eliminated, with adequate research.

However, conducting market research is a lot harder than it seems. With the overwhelming amount of data obtainable via the internet, it’s more challenging to siphon what’s relevant and beneficial for growing your business.

To ensure your success, below are five of the best market research strategies and resources you can leverage:

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7 Digital Marketing Trends To Keep in Mind During 2017

Don’t you hate feeling out of the loop?

We’re done with Q2 now, if you can believe it. Writing an article about what trends to look out for in 2017 might seem a bit overdo. But for a lot of companies, particularly small companies and startups, Q1 can be largely spent collecting your bearings and strategizing for the coming year.

So at the onset of Q2, it doesn’t hurt to take stock of what the current digital marketing trends are. You might find you need to refocus your digital marketing strategy, especially if something wasn’t working in Q1.

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Attention Grabbing: Add Some Gusto To Your Company Online Content

 

How do you find your place during these days where we are privy to an infinite amount of information on the World Wide Web?  What do you do to jump out and grab your share of the business when you feel you are just one of the littler guys?

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4 questions to help decide between working at a startup and a tech giant, from a former Google engineer

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4 questions to help decide between working at a startup and a tech giant, from a former Google engineer

Nikola Otasevic has pretty much done it all when it comes to software engineering.

He earned a BS in both electrical engineering and computer science and economics, as well as a master’s in engineering from MIT. He interned at Microsoft in college, and also worked at MIT as a research assistant. He spent a summer as a technology associate at Bridgewater. He gained experience at smaller firms like Room 77, which was acquired by Google in 2014. Until 2016, he worked at Google as a software engineer.

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What Is Internet Marketing? Advice From An Eight-Figure Earner

The allure of so-called internet riches is nothing new. At every bend and turn in a gauntlet of online gurus, you’ll find internet marketers looking to hype up this supposed dream of making money online or earning passive income while kicking up your feet and letting the cash roll in. While internet marketing doesn’t quite work that way, in that you actually do have to put in the work, it isn’t too difficult to separate the proverbial men from the boys when it comes to the real online earners.

The Truth? You don’t often come across genuine individuals in this space. I could likely count on one hand who those genuine-minded marketers might be. Someone like Russel Brunson who’s developed a career out of providing true value in the field and helping to educate the uneducated is one such name. However, while Brunson has built a colossal business, the story of David Sharpe and his journey to becoming an 8-figure earner really hits home for most people.

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Serving citizens better with Big Data

From helping public libraries target specific groups of borrowers to catching rogue MRT trains, the possibilities are endless when government agencies use data science for the public good.

Speaking on 1 March at the Big Data & Analytics Innovation Summit 2017, Mr Liu Feng-Yuan, Director of GovTech’s Government Digital Services (GDS) Data Science Division, pointed to these examples to illustrate the Singapore government’s efforts at using data to drive decision making.

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