In the times when data is of extreme value, industries cannot afford to ignore it. The only right choice for them is to find new ways to use data for their benefit.

These words have become a motto for the sales industry along with the others. As far as the feature of the…

Summary:  AI/ML itself is the next big thing for many fields if you’re on the outside looking in.  But if you’re a data scientist it’s possible to see those advancements that will propel AI/ML to its next phase of utility.

“The Next Big Thing in AI/ML is…” as the lead to an article is probably the most…

Actually the unlocking of hidden benefits and true potential of the data is an essential task for business. Also, customers` satisfaction appears to be a pushing force for evolution of services and products. If you have loads of customer data available for analysis the work on the improvement of the customers` satisfaction…

Q1. Is MSc in Data science/Data Analytics same as ML/AI as some universities don’t have AI but Data Science?

Q2. I am interested in MS Data Science and not MS Analytics as the later is not technical in nature. Are MS Data Science and MS Data Analytics the same?

Q3. How to Choose Between a Master’s in Data Analytics vs Business…

By Stefan Stoyanov, Business Analytics & Research Intern at Boemska

I started my MSc Business Analytics course at theh University of Surrey almost one year ago. I had no prior experience in Machine Learning or data science. Before, I used to develop and manage EU projects…

Let’s explore the complexity and vulnerability of IT infrastructure and how to build a modern IT infrastructure monitoring solution, using a combination of time series databases with machine learning.

IT Infrastructure: Complex and Vulnerable…

Data is the new fuel- it drives businesses towards exponential growths. It has the power to transform operational and add intelligent insights with its immense potential. The key, however, lies with understanding data and its insights.

Logistics, like other domains, can also leverage from the several advantages of data. It all begins with what to do with the collected data. Data Science will come into the picture with its amalgamation of statistical &…

If you are a recent graduate or someone preparing for your first data scientist position, then here are some tips to help you ace your interview!…

Summary:  More data means better models but we may be crossing over a line into what the public can tolerate, both in the types of data collected and our use of it.  The public seems divided.  Targeted advertising is good but the increased invasion of privacy is bad.

Headlines are full of alarm.  The public is up in arms.  The internet is stealing their privacy.  Indeed, the Future of Humanity Institute at Oxford rates this as the most…

The energy sector is under constant development, and more of significant inventions and innovations are yet to come. The energy use has always been involved in other industries like agriculture, manufacturing, transportation, and many others. Thus these industries tend to enlarge…

Our model for recognizing specific animals in images is a neural network consisting of multiple layers, and the initial layers are already good at understanding the world in general. So instead of “re-inventing the wheel,” we only need to train the final layers.

I was excited to work on a recent project with one of our partners, Wild Detect, because it aligns with one of our goals at Appsilon — to use data science consulting to aid in the…

Summary:  Despite our concerns about China taking the lead in AI, our own government efforts mostly through DARPA continue powerful leadership and funding to maintain our lead.  Here’s their plan to maintain that lead over the next decade. 

Think all those great ideas that have powered AI/ML for the…

Summary:  If you are guiding your company’s digital journey, to what extent should you be advising them to adopt deep learning AI methods versus traditional and mature machine learning techniques.

By now everyone is at least familiar with using AI/ML as a required cornerstone of company strategy.  Frequently…

Emerging applications like machine learning (ML), big data analytics, and artificial intelligence (AI) has created the need for many companies to hire highly skilled and experienced work force. Demand for data scientists, ML engineers and data engineers is booming and will only increase in the next years. The January report from Indeed, one of the top job sites, showed a 29% increase in demand for data scientists year over year and a 344% increase since 2013.

Salaries and…

Machine learning applications require powerful and scalable computing systems that can sustain the high computation complexity of these applications. Companies that are working on the domain of machine learning have to allocate a significant amount of their budget for the OpEx of machine learning applications whether this is done on cloud or on-prem.

Typical machine learning application…

Summary: Especially in consumer goods and retail the value of AI/ML is only part of the story.  AI/ML will increasingly need to integrate with helper technologies to deliver maximum value.  Up your game in IoT, 5G, and robotics to ensure you’re giving your operating team all the best options for their investment.

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