As many applications are getting ready for invasion of Containerization, there is a side conversation that picked up talking of sunset of the same. Let’s see if we are moving towards it!

Witnessing the spark that Containerization brought-in from Virtualization, the Software Development didn’t only realize the benefits such as well-managed, Independent application stacks, better use of OS Kernels, lightweight execution environments en masse — but also, tweaked unparalleled advantage of achieving Scalability, Composability, Portability and right degree of Isolation that application needs.

In this article, we will surface few basic constructs of Containers that popularised them and discuss the…

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Photo by Kozjat

Cloud-native Micro-service development being the focus area, we will discuss and build a sample end-to-end Java application by leveraging the benefits of super cool tech-stack such as:

  • Visual Studio Code as piggybacking IDE
  • Spring Boot
  • Docker
  • Kubernetes

VS Code as single IDE

Far too long, Java developers did give oversight of picking up and exploring VS Code for Java development. When I stumbled upon this IDE, I felt this editor has decent enough support. However, we will uncover VS Code features for all-inclusive development of our goal in step-by-step manner.

Once you have downloaded the IDE into your laptop, you can search and download the…

Math is Force-Multiplier in Data Science!

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If you wanted to be a data scientist, you would need to deal with mathematics on daily basis. But, how much math one should know? Well, dozen people have dozen different answers for this question. I would say - you don’t have to be a math-nerd but with solid foundations. Therefore, here, we will only focus getting to the meat and practicing Algebra which is essential for data science. All you need is solid interest, quality time and local python environment.

Algebra helps get better hold of Linear/Polynomial/Logistic Regression and many other areas.

Let’s hit the high spots!

Like…

Ability to see things ahead of ‘time’ is key to success.

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What does it take to build a time-machine from you as a data scientist? All you need is ‘Time’. Don’t you?

What’s key in businesses is to make Informed Decisions which most of the times will be driven by ‘Time Series Forecasting’. It involves breaking time component into decades, years, months, hours, minutes and possibly seconds. They reveal decent hidden insights when you view them in part and in groups.

Difference between Prediction and Forecasting

Forecasting is a process of predicting or estimating future events based on past and…

LaxmiKumar Reddy Sammeta

Learner | Coder | Contributor | Challenger

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