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Thrust Areas of Machine Learning and Its Current Scenario

M. Vasumathy1

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-10 , Page no. 121-123, Oct-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i10.121123

Online published on Oct 31, 2019

Copyright © M. Vasumathy . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: M. Vasumathy, “Thrust Areas of Machine Learning and Its Current Scenario,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.10, pp.121-123, 2019.

MLA Style Citation: M. Vasumathy "Thrust Areas of Machine Learning and Its Current Scenario." International Journal of Computer Sciences and Engineering 7.10 (2019): 121-123.

APA Style Citation: M. Vasumathy, (2019). Thrust Areas of Machine Learning and Its Current Scenario. International Journal of Computer Sciences and Engineering, 7(10), 121-123.

BibTex Style Citation:
@article{Vasumathy_2019,
author = {M. Vasumathy},
title = {Thrust Areas of Machine Learning and Its Current Scenario},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2019},
volume = {7},
Issue = {10},
month = {10},
year = {2019},
issn = {2347-2693},
pages = {121-123},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4906},
doi = {https://doi.org/10.26438/ijcse/v7i10.121123}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i10.121123}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4906
TI - Thrust Areas of Machine Learning and Its Current Scenario
T2 - International Journal of Computer Sciences and Engineering
AU - M. Vasumathy
PY - 2019
DA - 2019/10/31
PB - IJCSE, Indore, INDIA
SP - 121-123
IS - 10
VL - 7
SN - 2347-2693
ER -

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Abstract

Machine Learning counter in this world beyond the buzzwords to transfigure our living cosmoses. It is made conceivable by the convergence of lively data. Traditionally, Machine learning (ML) is multi-disciplinary inclusive of statistics and computer science in around of computational systems from the collective data prediction than instructions. ML functions to the base fact of predictions of data on the reality of applications. Thence the thrust areas of Machine Learning with its bias are explicated here with certain reality and comprehensive examples like Trusting Scientific Discoveries Made Possible, Facing Volatile Price Trends for Tomato Growers, Gaining Critical Mass for Data Analytics Pros and Finding Hidden Technologies in IIOT. The techno ML is majorly bounded with rule and behavior-based systems, Bayesian and statistical algorithm, Neural Network and Deep Neural Network are also exposed here with their specification and its learning style is deliberated.

Key-Words / Index Term

Machince Learning, Scenario of ML, Analytics, Techno ML, IIOT, Neural Network

References

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[3] https://www.thehindubusinessline.com/economy/agri-business/karnataka-tomato-growers-to-get-crop-price-forecasts-from-ibm-using-ai-ml/article26358330.ece
[4] Alvaro F. Fuentes, Sook Yoon, Jaesu Lee, and Dong Sun Park, “ High-Performance Deep Neural Network-Based Tomato Plant Diseases and Pests Diagnosis System With Refinement Filter Bank, 2018 Aug 29. doi: 10.3389/fpls.2018.01162
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