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Shifting Towards Intelligent Technology (Deep Learning)-An Incredible Move in Talent Acquisition

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By

Vinay Johar, CEO - Rchilli Inc.


I find it amazing how HR technology is making advancements to provide remarkable improvement in the recruitment process. AI, machine learning, deep learning are the concepts which are surprising us with new developments. Using them in our recruitment process is not only simplifying the same but also help us in fetching quality talent. 


But do you know all these terms have a different meaning? 

Yes, most people see these concepts as another technical term, but there is a difference. While AI can speak or process text-based conversations, machine learning is when computer systems use algorithms to perform tasks. 

On the other hand, deep learning is a part of machine learning family and is based on artificial neural networks.

According to Moor Insights & Strategy, “Deep learning requires large amounts of data to be fed into the processor without making the processors wait for that data.


HR technology providers are adopting deep learning technology to let the recruitment process deliver effective results. RChilli takes pleasure in announcing the launch of its deep learning resume parsing module. 


Also Read: Launching the Powerful Deep Learning Resume Parsing Module


Deep Learning-A Great Move in Acquiring Quality Talent

Deep learning is a game-changer in almost every industry, including HR, healthcare, financial services, retail, etc. 

Talking about recruitment, parsing resumes with precision, and perfection requires the use of latest and best-in-class technologies. This is where deep learning plays an important role. 



How Does It Help?

Want to discover how this latest technology can bring satisfying results? 

Deep learning broadens the scope of resume parsing. It processes a large amount of data by using algorithms. As a result, it promotes smarter identification of resume data, which results in lesser error rates. 

Also, deep learning has the capability of finding patterns in data automatically. It is a new milestone which marks the beginning of faster improvements and developments in a resume parser. 

It simplifies the process of adding new knowledge. Earlier, a parser worked by gathering the skills manually, but deep learning automates this process. 


What Does It Take to Build A Parser?

Building a resume parser requires the use of a comprehensive set of technologies at the backend. The team at RChilli has spent a lot of years researching in AI, NLP, and machine learning to analyze how these will improve recruitment.  

Would you like to see which technologies form a part of RChilli’s technology stack? Check out the above image.


Published on LinkedIn here


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