First posted on Dev Letters
This Dev Letter is a bit different. Today, we have Navneet Nandan, who is a Data Science professional and he is sharing some insights about his career.
Data Science is a fantastic discipline with almost unlimited possibilities, and I am sure, like me, you are also interested in learning how it feels to be a professional in the same.
What do you do?
I am an NLP engineer at Mettl, a company which provides online assessments for recruitment tests and much more. I handle most of the work related to 'text' there, for example, automate long answer type questions evaluation, parsing resumes and job descriptions, etc.
What do you think is about Natural Language Processing that attracts you to it?
As text is the most common form of input on the web, there is always a lot of data to analyze and extract meaningful information from.
Natural Language Processing is not a new field, but it got a big push in recent years due to advancements in the field of machine learning and deep learning. This created new opportunities to solve a variety of problems.
This makes my work interesting, I get to solve many challenges which are unexplored or less explored and impact our lives a lot. For example, many of us want to read the summary of a news article in our local language, but neither there are sufficient news sources in our local languages nor automatic summarization for them is available. There is a need to have a system which can gather news sources from a variety of sources and summarize it in our local languages, for example, Hindi.
Similarly, there are plenty of new interesting problems which can be solved, and there are plenty of existing problems whose solutions can be improved.
Challenges and opportunities in NLP are endless.
Where do you see yourself in 2 years?
I am enjoying my time here at Mettl presently, solving some of the real-life problems and easing the task of recruitments.
In the coming years, I would like to become part of some of the leading research labs of India, like Microsoft Research, IBM Watson, Google etc. and contribute more to solve problems of the common people of India, especially breaking the language barrier.
Any comments on other rising technologies and how do you see it being used with NLP in the future?
There has been a lot of new technology developments in recent years, ranging from Artificial Intelligence to Virtual Reality and Augmented Reality to Blockchains.
NLP is one of the driving forces of artificial intelligence as most of the input is given in human language. Until computers are not able to completely understand the human language, we cannot make a sound intelligent system which can interact with humans or follow their directions.
In the field of VR and AR, I don't think NLP is going to contribute much.
Applying blockchains and NLP together is very new right now, but blockchains are helping to decentralize the whole AI platform by (for example) making truly personal assistant with fewer security concerns. Doc.ai has interesting applications combining blockchain and NLP to create the first Blockchain-Enabled Natural Language Processing Platform for Quantified Biology (link).
How should a beginner go about starting learning NLP?
Beginners can start learning from various MOOCs available online, but I would personally suggest “CS224n: Natural Language Processing with Deep Learning” course from Stanford University. This would help you understand the basics and applications of both, NLP and Deep Learning.
Also, if you are comfortable with Python, then you should learn the NLTK library and if you use Java, then go with Stanford CoreNLP library. These libraries would help you implement NLP applications.
Where can the readers contact you?
Readers may contact me on Twitter (@navneetnandan8), Gmail (navneetnandan8), and connect with me on LinkedIn.
Top comments (1)
I also believe there is a huge gap in the recruitment process support that NLP can fill it. So my question would be what are sources or ready to use tools that hit this topic. Like Resume analysis, resume to job matching
Thank you!