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Data science teams are multidisciplinary, each with different skills and technologies of choice. Some of them use SAS, others may have analytical assets already built in Python or R. Let’s just say each team is unique. As part of our Continuous Integration/Continuous Delivery with monthly releases,... Read more
5 Unexpected Industries Utilizing AI and ML
Artificial intelligence (AI) and machine learning (ML) are changing the world around us in extraordinary ways, including some surprising new applications in global industries. These technologies enable us to take computing to a whole new level, which opens the door for innovations that improve processing capabilities,... Read more
6 Vital Parts of Data Processing
Big data is becoming more prevalent in the business landscape. The global market is expected to reach an estimated $103 billion by 2027. The world of vast information is complex and often ambiguous to the average person. Companies need to leverage data to remain competitive in... Read more
How to Create a Kubernetes Cluster Using Minikube
Using Kubernetes, we can handle a cluster of servers as one big logical server that runs our containers. We declare a desired state for the Kubernetes cluster, and it ensures that the actual state is the same as the desired state at all times, provided that... Read more
Understanding the “Machine Learning Way” to Solve Business Problems through Real-World Scenarios 
Ironically, one of the foremost barriers preventing the exploitation of machine learning in a business is neither the implementation of the algorithm nor the retrieval of the data (the how): the toughest part is to recognize the right occasion to use it (the why)! We need to... Read more
6 Business-Friendly Data Analysis Solutions
Nowadays, you may hear about big data and machines taking over the lives of people worldwide. From artificial intelligence (AI) to coding to computer science, and so on, technology has ushered in miracles and advancements that might not have been anticipated years ago. In addition, various... Read more
Systems built with software can be fragile. While the software is highly predictable, the runtime context can provide unexpected inputs and situations. Devices fail, networks are unreliable, mere anarchy is loosed on our application. We need to have a way to work around the spectrum of... Read more
The Rapid Evolution of the Canonical Stack for Machine Learning
Just a few years ago, almost nobody was building software to support the surge of new machine learning apps coming into production all over the world.  Every big tech company, like Google, Lyft, Microsoft, and Amazon rolled their own AI/ML tech stack from scratch.  See the... Read more
Top 5 Applications of Machine Learning in Healthcare
Machine learning (ML) is a branch of artificial intelligence (AI), where computer systems independently find solutions to complex problems using recurring patterns in databases. Put differently, machine learning helps IT systems to recognize patterns from existing algorithms and datasets, then go ahead and develop appropriate solutions.... Read more
Decoupling Complex Systems with Event Driven Python Programming
We often think about events as ordered points in time that happen one after another, often with some kind of cause-effect relationship. But, in programming, events are often understood a bit differently. They are not necessarily “things that happen.” Events in programming are more often understood... Read more