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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Artificial intelligence (AI) seemingly has been discussed everywhere over the last few years, and now it’s made its way into the commercial insurance industry. Organizations are using AI and machine learning for everything from streamlining operations to offering more personalized care and better customer service. There is an increasing sense of urgency about getting started on the AI journey. The question is how. Do they develop a custom solution in-house or purchase a third-party solution…

Summary:  Communicating with your Board of Directors about AI/ML is different from conversations with top operating executive.  It’s increasingly likely your Board will want to know more and planning that communication in advance will make your presentation more successful.

As AI/ML becomes increasingly…

Imagine you’re completing a mission in a computer game. Maybe you’re going through a military depot to find a secret weapon. You get points for the right actions (killing an enemy) and lose them for the wrong ones (falling into a pit or getting hit). If you’re playing on high difficulty, you might not conclude this task in just one attempt. Try after try, you learn which consecutive actions are needed to get out of a location safe, armed, and equipped with bonuses like extra health points or…

Experiments

In his book, The Master Algorithm, Pedro Domingos imagines the following experiments:  

Take a building, extremely well–built for two purposes: Nothing can enter and most importantly nothing can…

Artificial Intelligence might not be the newest entrant in smart technology but, its redefined usage is. It has recently gained mass popularity. Now, it is being accepted across many industries. With the general public embracing AI, government agencies are also considering this fantastic technology. AI can imitate human's decision-making skills. Thus, it has the potential to improve the decision-making ability of various applications. The AI engine is useful for multiple applications such…

We have been in existence for over 10 years now, with content in many different places, lists, categories, and databases. This is an attempt to put everything together in one place, and help our readers (re-)discover some great articles and resources that were lost on the Internet over the years, but still sit on our web servers. We are making them come back to life. We are in the process of organizing it in a way that is user-friendly.  Some of the resources below are very recent, and some…

We investigate a large class of auto-correlated, stationary time series, proposing a new statistical test to measure departure from the base model, known as Brownian motion. We also discuss a methodology to deconstruct these time series, in order to identify the root mechanism that generates the observations. The time series studied here can be discrete or continuous in time, they  can have various degrees of smoothness (typically measured using the Hurst exponent) as well as long-range or…

Machine Learning (ML) has been among the top strategies for almost every organization - whoever adopts the new methodology early and quickly establishes the corporate capability will gain competitive advantages in the market. 

However, because ML is still a relatively new field and data science is a skillset that is scarce for many companies, how to make the journey move at optimal speed without disaster or time wasted…

BigQuery is Google’s serverless, highly scalable, enterprise data warehouse designed to make all your data analysts productive at an unmatched price-performance. Because there is no infrastructure to manage, you can focus on analyzing data to find meaningful insights using familiar SQL without the need for a database administrator.

Analyze all your data by…

Summary:  Based on a McKinsey study we reported that 47% of companies had at least one AI/ML implementation in place.  Looking back at the data and the dominance of RPA as the most widely reported instance makes us think that the number is probably significantly lower.

We’ve been trying to get a handle on…

We’ve all experienced the great data rush as companies push to use analytics to drive business decisions. After all, the proliferation of data and its intelligent analysis can change entire company trajectories. But to make the quintillions of data created each day truly useful, as well as all that has come before, it must be understandable to an artificial intelligence (AI) system.

Dealing with numbers is one thing, but human language is…

Summary:  In the literal blink of an eye, image-based AI has gone from high cost, high risk projects to quick and reasonably reliable.  C-level execs looking for AI techniques to exploit need to revisit their assumptions and move these up the list.  Here’s what’s changed.

For data scientists these are miraculous times.  We tend to think of miracles as something that occurs instantaneously but in our world that’s not quite so.  Still the rate…

Data Science is a combination of data inference, algorithms, and technology that solves complex problems. The core of this technology is data that is initially raw, then is streamlined, and stored in a data warehouse. These vast amounts of data can help generate significant business values.…

Summary:  Adoption of AI/ML by larger companies has more than doubled since last year according to these survey results from McKinsey and Stanford’s Human-Centered AI Institute.  This new data gives us a much better idea of which global regions and which industries are adopting which AI/ML techniques.

We know…

Visualization has become a key application of data science in the telecommunications industry.

Specifically, telecommunication analysis is highly dependent on the use of geospatial data. This is because telecommunication networks in themselves are geographically dispersed, and analysis of such dispersions can yield valuable insights regarding network structures, consumer demand and availability.

Data

To illustrate this point, a k-means clustering algorithm is used…