The release of Hadoop 3 in December 2017 marked the beginning of a new era for data science. The Hadoop framework is at the core of the entire Hadoop ecosystem, and various other libraries strongly depend on it.

In this article, we will discuss the major changes in Hadoop 3 when compared to…

Table of Contents:

• Chatbots: What are they today?
• Why, Where, and When to Use…

Medicine and healthcare is a revolutionary and promising industry for implementing the data science solutions. Data analytics is moving the medical science to a whole new level, from computerizing medical records to drug discovery and genetic disease exploration. And this is just the beginning.…

Using data science in the banking industry is more than a trend, it has become a necessity to keep up with the competition. Banks have to realize that big data technologies can help them focus their resources efficiently, make smarter decisions, and improve performance.

Here is a list of…

In our last post, we explained the basics of streaming with Spark. Today, we want to talk about graphs and explore …

What is computer vision?

Nowadays, computer vision (CV) is one of the most widely used dimensions of machine learning. The main task of computer vision is to understand the contents of the image. It is used almost in all spheres of…

Nowadays, text processing is developing rapidly, and several big companies provide their products which help to deal successfully with diverse text processing tasks. In case you need to do some text processing there are 2 options available. The first one is to develop the entire system on your own from scratch. This way proves to be very time and…

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Nowadays, there is a huge list of powerful visualization tools to help you illustrate your ideas,…

In our previous articles, we have discussed the top Python libraries for data science. This time we will focus on Scala, which has recently become another prominent language for data scientists. It has gained popularity mostly due to the rise of Spark,…