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Emerging trends in machine learning
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Journal of Computer Science & Systems Biology

ISSN: 0974-7230

Open Access

Emerging trends in machine learning


Joint Event on 5th World Machine Learning and Deep Learning Congress and World Congress on Computer Science, Machine Learning and Big Data

August 30-31, 2018 Dubai, UAE

Manoj Mishra

Union Insurance, UAE

Scientific Tracks Abstracts: J Comput Sci Syst Biol

Abstract :

In this time of immense machine learning skills shortage, Data and analytics leaders face a dilemma. Without data scientists, venturing into machine learning and data science is difficult. Without any successful pilots, convincing the business to hire data scientists is equally challenging. Auto ML is a concept started by H2o which has been recently gone to the next level by Google's Automated Machine Learning which lets you train custom machine learning models without having to code. My workshop will be focusing on these trends in a little more detail and also a demo on how these trends can be leveraged.

Biography :

A distinguished Technology leader driving transformation through innovation in Data Engineering, Data Management and Data Science. Holds a “Bachelor Of Engineering” in Computer Science and a certification in “Data Science” from “Johns Hopkins University” Transformational leader, with a track record of developing solutions for future, creating benchmark of performance and success. More than two decade of experience spreading across multiple geographies (US, Europe, India and Middle East) working with Organizations like Adobe Systems, Dell, Perot Systems, CEB-Gartner, Rolta and Tata Group. Moved to Dubai in June 2017 to take a leadership role as “Chief Manager–Business Intelligence & Data” with Union Insurance and currently leading their Data Strategy and Technology Transformations through Data, Analytics, research & various AI initiatives.

E-mail: manumishra2001@gmail.com

 

Google Scholar citation report
Citations: 2279

Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report

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