Welcome to the second chapter from the NLP Grimoire series. In the last chapter, we learned what NLP is all about and what are some tasks we usually do in NLP, along with some common applications of NLP. In this chapter, we will discuss the process of selecting an appropriate…

Welcome to the first chapter of the NLP Grimoire! A series that will enable its diligent readers to harness the power of NLP and create cosmically powerful applications. All you need to know is some Python programming. This chapter will be a little more theoretical but it is suggested to…

The Machine Learning landscape is in a state of continuous change. New research, technologies and tools are put out every day. This sometimes makes it hard to keep up with the latest trends. Besides that, the vastness of the domain can induce the imposter syndrome in practitioners. …

There are multiple tools available over the internet to check the similarity of a claim or a patent. There are pros and cons of every tool and a user can sometimes have a hard time deciding what to use where. In such situations, people tend to use the services they…

In a data-driven organization, there is a constant need to provide vast amounts of data to the teams. There are many tools available to aid your requirements and needs. Choosing the right tool can be a little challenging and overwhelming at times. …

If you are a growing data-driven organization, you might have been working to harvest large amounts of data to extract valuable insights from it. This can be costly and inefficient unless the data science team adopts the repeatable solutions to common problems. Although the specifics of organizations may vary, the…