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Impact of Machine Learning on Technology and Society
Submission Deadline: Dec. 20, 2019

This special issue currently is open for paper submission and guest editor application.

Join as Guest Editor Submit to Special Issue
Lead Guest Editor
Kriti Srivastava
Dwarkadas J Sanghvi College of Engineering, Maharashtra, India
Guest Editors
  • Sindhu Nair
    Dwarkadas J Sanghvi College of Engineering, Maharashtra, India
  • Pratik Kanani
    Dwarkadas J Sanghvi College of Engineering, Maharashtra, India
  • Neha Katre
    Dwarkadas J Sanghvi College of Engineering, Maharashtra, India
  • Nancy Nadar
    Dwarkadas J Sanghvi College of Engineering, Maharashtra, India
  • Sudhir Bagul
    Dwarkadas J Sanghvi College of Engineering, Maharashtra, India
  • Ramchandra Mangrulkar
    Dwarkadas J Sanghvi College of Engineering, Maharashtra, India
Guidelines for Submission
Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.
Papers should be formatted according to the guidelines for authors (see: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=183). By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at http://www.sciencepublishinggroup.com/login. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.
Published Papers
The special issue currently is open for paper submission. Potential authors are humbly requested to submit an electronic copy of their complete manuscript by clicking here.

Special Issue Flyer (PDF)

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Special Issue

Introduction
In today’s world we are floating in huge data due to technology advancement. Analyzing data, learning the hidden information and using them to improve the prediction accuracy can be extremely useful for further technology innovation. Using various learning methods, data can be used to build models which can be used in different walks of life and impact society in a positive way. We invite researcher to contribute their original work in the area of machine learning.

Aims and Scope:

  1. machine learning
  2. data analysis
  3. data mining
  4. image processing
  5. health care and machine learning
  6. sensor data analysis
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