Deep Machine Learning

Author:

Giri Parimal Kumar1,Mallick Chandrakant1,Mishra Sambit Kumar2

Affiliation:

1. Gandhi Institute of Technological Advancement, India

2. Gandhi Institute for Education and Technology, India

Abstract

With deep learning technology, machine learning has shown impressive results. Nonetheless, these techniques frequently use excessive amounts of resources; they demand big datasets, a lot of parameters, and a lot of processing power. In order to develop machine learning models that are efficient with resources, the authors have outlined a general machine learning technique in this work that they call deep machine learning. All the methods that initially identify inductive biases and then use those inductive biases to improve the learning efficiency of models come under the umbrella of deep machine learning. Numerous robust machine learning techniques are currently in use, and some of them are highly well-liked precisely because of their efficacy. Deep machine learning, however, is still in its infancy, and much more work remains. The efforts must be focused in order to progress artificial intelligence (AI).

Publisher

IGI Global

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3