- Substitution represents basic IT modernization; such as leveraging new…
The insurance industry – one of the least digitalized – is not surprisingly one of the most ineffective segments of the financial services industry. Internal business processes are often duplicated, bureaucratized, and time-consuming. As the ubiquity of machine learning and artificial intelligence systems increases, they have the potential to automate operations in insurance companies thereby cutting costs and increasing productivity. However, organizations have plenty of reasons to resist…Continue
Added by Denys Harnat on August 28, 2018 at 3:35am — No Comments
In last part we have seen the basics of Artificial intelligence and Artificial Neural Networks. As mentioned in the last part this part will be focused on applications of Artificial neural networks. ANN is very vast concept and we can find its…Continue
Added by Jayesh Bapu Ahire on August 25, 2018 at 9:00pm — No Comments
Summary: IBM’s Watson QAM (Question Answering Machine), famous for its 2011 Jeopardy win was supposed to bring huge payoffs in healthcare. Instead both IBM and its Watson Healthcare customers are rapidly paring back these projects that have largely failed to pay off. Watson was the first big out-of-the-box commercial application in ML/AI. Has it become obsolete?
Added by William Vorhies on August 21, 2018 at 10:51am — No Comments
Machine learning in finance may work magic, even though there is no magic behind it (well, maybe just a little bit). Still, the success of machine learning project depends more on building efficient infrastructure, collecting suitable datasets, and applying the right algorithms.
Machine learning is making significant inroads in the financial services industry. Let’s see why financial companies should care, what solutions they can implement with AI and machine learning, and how exactly…Continue
Added by Tetiana Boichenko on July 13, 2018 at 4:12am — No Comments
The best trained soldiers can’t fulfill their mission empty-handed. Data scientists have their own weapons — machine learning (ML) software. There is already a cornucopia of articles listing reliable machine learning tools with in-depth descriptions of their functionality. Our goal, however, was to get the feedback of industry experts.
And that’s why we interviewed data science practitioners — gurus, really —regarding the useful tools they…Continue
Added by Kateryna Lytvynova on July 13, 2018 at 2:00am — No Comments
Amazon is every online retailer’s forbidding nightmare. Last year, it dominated 44 percent of the US eCommerce market and about 4 percent of all domestic retail sales. One Click Retail, an eCommerce analysis provider, explains its dominance with the fact that millennials, Amazon’s core demographic, are getting older and starting to spend more. Moreover, advanced marketing capabilities for sellers, developments in Alexa, and pioneering in applications of the hottest technologies make it…Continue
Added by Maryna Ivakhnenko on July 11, 2018 at 11:00pm — No Comments
What is an artificial intelligence (AI)?
Most of us can not imagine a single day without a computer. With the rapid development of technology, various devices that simplify people's lives become more accessible. This is also connected with modern computers, which are capable of providing impressive fast processing of information.
Modern business uses the full potential of information technology. This allows you to store important data and manage it…Continue
Added by Barbara Elliott on June 21, 2018 at 1:00am — No Comments
From the back cover:
Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more…Continue
In a previous blog I wrote about 6 potential applications of time series data. To recap, they are the following:
Here I am focusing on outlier…Continue
Added by Mab Alam on June 1, 2018 at 2:00pm — No Comments
Machine learning has the ability to automate a lot of jobs in the future. It is very easy to talk about this automation when it isn't your job that will be automated. But the scary part is that there are a lot of highly skilled jobs that will also face some type of automation in the future as well. When you are talking about your own job potentially being automated, it becomes less abstract and more real. It is very easy to say go ahead and automate jobs, until it is your own that is being…Continue
I’m sure you’ve probably heard about the 2018 FIFA Football World Cup in Russia everywhere during the last few months. And, if you are a techy too, I guess you also have realized that Machine Learning and Artificial Intelligence are buzzwords too. So, what better way to get ready for the World Cup than by practicing in a project that combines these two hot…Continue
Added by Regiane Folter on March 28, 2018 at 4:30am — No Comments
"No one wants to be sold but everyone wants to buy."
Most of us hate being sold. The moment we know someone is selling something, we keep our guards up.
In the book, The Challenger Sale, authors Mathew Dixon and Brent Adamson surveyed over 6000 salespeople from around the world and found that ‘challenger salespeople’ outperformed every other group. Who are these challenger salespeople? These…Continue
Added by Rudradeb Mitra on March 1, 2018 at 9:00pm — No Comments
Time series forecasting is hardly a new problem in data science and statistics. The term is self-explanatory and has been on business analysts’ agenda for decades now: The very first practices of time series analysis and forecasting trace back to the early 1920s.
The underlying idea of time series forecasting is to look at historical data from the time perspective, define the patterns, and yield short or long-term predictions on how – considering the captured patterns – target…Continue
Added by Olexander Kolisnykov on February 14, 2018 at 1:58am — No Comments
Data science has made its way into practically all facets of society – from retail and marketing, to travel and hospitality, to finance and insurance, to sports and entertainment, to defense, homeland security, cyber, and beyond. It is clear that data science has successfully sold its claim of "actionable insights from…Continue
In the past few years, machine learning (ML) has revolutionized the way we do business. A disruptive breakthrough that differentiates machine learning from other approaches to automation is a step away from the rules-based programming. ML algorithms allowed engineers to leverage data without explicitly programming machines to follow specific paths of problem-solving. Instead, machines themselves arrive at the right answers based on the data they have. This capability made business…Continue
I have been looking to create this list for a while now. There are many people on quora who ask me how I started in the data science field. And so I wanted to create this reference.
To be frank, when I first started learning it all looked very utopian and out of the world. The Andrew Ng course felt like black magic. And it still doesn't cease to amaze me. After all, we are predicting the future. Take the case of Nate Silver - What else can you call his success if not Black…Continue
Added by dataperspective on November 15, 2017 at 1:30am — No Comments
The research firm Technology Business Research (TBR) recently came out with a report titled, “Winning The Business Of Digital Transformation Services Requires A Process-Led Approach” authored by Sebastian Lagana and Jennifer Hamel. The report is full of good nuggets, but I especially liked the way that they categorized the 3 phases of Digital Transformation:
Added by Bill Schmarzo on November 12, 2017 at 5:00am — No Comments
When I was beginning my way in data science, I often faced the problem of choosing the most appropriate algorithm for my specific problem. If you’re like me, when you open some article about machine learning algorithms, you see dozens of detailed descriptions. The paradox is that they don’t ease the choice.
In this article, I will try to explain basic concepts and give some intuition of using different…Continue
Added by Luba Belokon on October 26, 2017 at 6:00am — No Comments