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Introduction

  • Bin Shi
  • S. S. Iyengar
Chapter

Abstract

Learning has various definitions based on the context in which it is used and the various entities involved in the learning process. The need for machines to learn and thus adapt to the changes in its surroundings led to the rise of the field aptly called “machine learning.” A machine is expected to learn and predict the future outcomes based on the changes that it notices in the external structure, data/inputs fed that would have to be responded to, and the program/function it was built to perform. This forms the basis for the various complex computational capabilities that any modern artificially intelligent based (AI-based) system would require and includes computations dealing with recognition of patterns, diagnosis of data, controlling the system or environment, planning activities, etc.

Keywords

Machine learning (ML) Neural networks Convolutional neural networks Recurrent neural networks Deep learning Gradient descent 

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Bin Shi
    • 1
  • S. S. Iyengar
    • 2
  1. 1.University of CaliforniaBerkeleyUSA
  2. 2.Florida International UniversityMiamiUSA

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