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Machine learning intersections and challenges in deep learning

Bhavana Jamalpur, Seena Naik Korra, R. Vijaya Prakash, E. C. G. Sudarshan, Bonthala Prabhanjan Yadav

2020IOP Conference Series Materials Science and Engineering31 citationsDOIOpen Access PDF

Abstract

Abstract Deep learning is certainly not a limited finding tactic, however, it follows several procedures and also topographies which could be associated with a huge speculum of complex problems. The strategy knows the illustrator in addition to differential attributes in a stratified way. Deep learning strategies have created a notable innovation along with sizable effectiveness in an assortment of applications with useful protection units. It is taken into account to become the greatest choice for revealing the architecture in high-dimensional relevant information by using a backpropagation process and concepts analysis. As deep learning has assisted help make significant advancements and also significant performance in many therapies, the wide-spread domain names of deep learning are service, scientific study, cancer cells diagnosis, natural language processing, medical diagnosis, handwriting recognition, trumpet call recognition, stock market study. This paper provides the intersections towards machine learning and also the challenges of deep learning.

Topics & Concepts

Deep learningArtificial intelligenceComputer scienceMachine learningHandwritingArchitectureProcess (computing)Domain (mathematical analysis)BackpropagationArtificial neural networkData scienceArtVisual artsMathematicsMathematical analysisOperating systemBrain Tumor Detection and ClassificationCOVID-19 diagnosis using AIDigital Imaging for Blood Diseases
Machine learning intersections and challenges in deep learning | Litcius