This week you'll learn about Introduction to Natural Language Processing (NLP).

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As we step into a new era of Natural Language Processing (NLP) with Transformers, the bare beginnings should not be forgotten. NLP started as a mammoth task for computers, considering the amount of computation it would theoretically require. However, as technology progressed, we caught up with NLP's requirements and now have models which can flawlessly converse with humans without the latter realizing. 

Today, we aim to walk through the salient moments in history when step-by-step, progress was being made to take NLP to heights unimaginable. 

The big picture: We glance at the history of NLP and its beginnings. 

How it works: There have been several approaches to NLP, paradigm-based, stepping into representation learning, etc. All of these have helped shape NLP into the revered domain it is today, helping humanity with many practical, real-life problems daily. 

Our thoughts: This blog serves as a preface/introduction to the beautiful world of NLP, as well as to what's to come next. We have planned to traverse the beautiful yet twisty turns of NLP and hope you like it. 

Yes, but: If you are already an NLP practitioner, this blog might not contain anything you don't already know. Nevertheless, visiting the roots of your day-to-day work may be a nice detour. 

Stay smart: And stay tuned for what's to come next! 

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Note: You may have missed this, but last Wednesday, we published a new post on Computer Vision and Deep Learning for Government.



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