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Prateek Khurana
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Prateek Khurana
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Page 2

Machine Learning Solutions: An 8 Step Implementation Guide

by Prateek Khurana
Current tools used to educate managers and executives to machine learning solutions are either too complicated or too confusing. Online guides are mostly theory thus making it difficult for actual implementation.
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Artificial Intelligence Usage In Medical Science

by Prateek Khurana
Medical science is one field where the amalgamation of AI and medical science can be used to bring about life-changing technologies. In fact, cognitive technology is being used in the healthcare industry in assistance and support roles.
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Moving From RPA To AI: Are You Prepared For It?

by Prateek Khurana
Enterprises need Artificial Intelligence for a true breakthrough in the way organizations are run and AI has the potential for groundbreaking business transformation.
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Enterprises Need To Automate Intelligently

by Prateek Khurana
Experts are certain that the new wave of digital transformation will adopt IA and reap maximum benefits of this modern technology. If the basics are in place, intelligent automation will become the new backbone of your enterprise.
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Robotic Process Automation: Expectations And Misfires

by Prateek Khurana 2 Comments
Implementing RPA is increasingly becoming an essential utility for various enterprises to stay ahead of competition and meet customer expectations but human challenges remain.
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Advantage RPA: Automation For Financial Institutions

by Prateek Khurana
Robotic Process Automation (RPA) is a potential differentiator. It can make institutions and their services stand out on various aspects and parameters to meet customer expectations and stay ahead of competition.
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RPA Myths Busted: Top 5 Fallacies

by Prateek Khurana
The buzz surrounding RPA has received a lot of attention but there are also some perspectives, speculations, and interpretations that spurt from lack of knowledge and fear of automation.
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Make Your Enterprise RPA Ready

by Prateek Khurana
RPA is suited for tasks that can be performed as per predefined algorithms, tasks that need high volumes of data to be accumulated, segregated or converted, and the ones that need to processed quickly with high accuracy
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