IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Survey on Intelligence Tools for Data Analytics

A Survey on Intelligence Tools for Data Analytics
View Sample PDF
Author(s): Shatakshi Singh (Mody University of Science and Technology, India), Kanika Gautam (Mody University of Science and Technology, India), Prachi Singhal (Mody University of Science and Technology, India), Sunil Kumar Jangir (Mody University of Science and Technology, India) and Manish Kumar (Mody University of Science and Technology, India)
Copyright: 2021
Pages: 23
Source title: Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics
Source Author(s)/Editor(s): Bhushan Patil (Independent Researcher, India) and Manisha Vohra (Independent Researcher, India)
DOI: 10.4018/978-1-7998-3053-5.ch005

Purchase

View A Survey on Intelligence Tools for Data Analytics on the publisher's website for pricing and purchasing information.

Abstract

The recent development in artificial intelligence is quite astounding in this decade. Especially, machine learning is one of the core subareas of AI. Also, ML field is an incessantly growing along with evolution and becomes a rise in its demand and importance. It transmogrified the way data is extracted, analyzed, and interpreted. Computers are trained to get in a self-training mode so that when new data is fed they can learn, grow, change, and develop themselves without explicit programming. It helps to make useful predictions that can guide better decisions in a real-life situation without human interference. Selection of ML tool is always a challenging task, since choosing an appropriate tool can end up saving time as well as making it faster and easier to provide any solution. This chapter provides a classification of various machine learning tools on the following aspects: for non-programmers, for model deployment, for Computer vision, natural language processing, and audio for reinforcement learning and data mining.

Related Content

M. Govindarajan. © 2021. 18 pages.
Manisha Vohra, Bhushan Patil. © 2021. 9 pages.
Pankaj Pathak, Samaya Pillai Iyengar, Minal Abhyankar. © 2021. 22 pages.
Ricardo A. Barrera-Cámara, Ana Canepa-Saenz, Jorge A. Ruiz-Vanoye, Alejandro Fuentes-Penna, Miguel Ángel Ruiz-Jaimes, Maria Beatriz Bernábe-Loranca. © 2021. 23 pages.
Shatakshi Singh, Kanika Gautam, Prachi Singhal, Sunil Kumar Jangir, Manish Kumar. © 2021. 23 pages.
Selvan C., S. R. Balasundaram. © 2021. 19 pages.
Tihana Škrinjarić, Boško Šego. © 2021. 34 pages.
Body Bottom