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MLDLRTA 2019 : “Machine Learning and Deep Learning in Real Time Applications”
MLDLRTA 2019 : “Machine Learning and Deep Learning in Real Time Applications”

MLDLRTA 2019 : “Machine Learning and Deep Learning in Real Time Applications”

N/A
Event Date: June 20, 2019 - January 10, 2020
Abstract Submission Deadline: August 04, 2019
Submission Deadline: October 10, 2019
Notification of Acceptance: November 30, 2019
Camera Ready Version Due: January 10, 2020




Call for Papers

Dear Academicians/Researchers/Practitioners,

We are floating this Call for Chapters based on your expertise in Artificial Intelligence & Machine Learning. Currently, we are in the process of editing a book entitled “Machine Learning and Deep Learning in Real-Time Applications” to be published by IGI Global (www.igi-global.com) scheduled for release in February,2020.
In order to strengthen the overall quality of this publication, we invite you to contribute chapters within the scope of this book. In compliance with the time and to bring out the volume as per schedule, we request you to submit a chapter proposal before 4 August, 2019. Other important dates are also mentioned in this announcement.

Topics Covered Recommended chapters are divided into two parts, but not limited to: Part 1: Advancements in Deep Learning
 Deep Learning Libraries
 Deep Learning with KERAS
 Deep Learning with PYTORCH
 Deep Learning with TENSORFLOW
 Deep Learning and Embedded Systems
 Adoption of Machine/Deep Learning in Cloud

Part 2: Multidisciplinary Applications of Machine/Deep Learning
 Machine Learning for Data Security
 Health and Medical improvements using Machine Learning
 Machine Learning in the Insurance Industry
 Applications of machine learning in energy and utilities
 Deep learning in smart grids
 Video & Image processing with deep learning
 Deep Learning Applications in Computer vision
 NLP using Deep Learning
 Deep Learning and Internet of Things
 Deep learning based smart agriculture



Credits and Sources

[1] MLDLRTA 2019 : “Machine Learning and Deep Learning in Real Time Applications”


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