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Machine Learning Algorithms and Applications

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air quality evaluation
Ambient intelligence
animal classifications
AnimNet
Anomaly detection
artificial intelligence
Association rule mining
Bayesian learning
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Cognitive intelligence
Computational intelligence
control and data mining
Convolutional Neural Network
Credit Scoring Model
Data pre-processing
Decision trees
deep learning
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Facial Expression recognition
Factor Analysis
fake profile detections
Feature extraction
Feature learning
Generative Adversarial Network
Independent Components Analysis
Intelligent systems
K-Means
L-Hidden Markov Models
Logistic regression
M-Factor Graphs
Machine learning
manufacturing products
Medical image analysis
Multi agent systems
Natural language processing
Network analysis
neural networks
pattern recognition
Pattern recognition for bioinformatics
Principal Components Analysis
Reinforcement learning
Res-SE-Net
Self-learning
Semi-supervised learning
sentiment analysis
silkworm counting
social networks
Sparse dictionary learning
Supervised learning
Support vector machines
Text recognition
Unsupervised learning
Wind Speed Prediction System

Product details

  • ISBN 9781119768852
  • Weight: 454g
  • Dimensions: 10 x 10mm
  • Publication Date: 28 Sep 2021
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms.

The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.
About

Mettu Srinivas PhD from the Indian Institute of Technology Hyderabad, and is currently an assistant professor in the Department of Computer Science and Engineering, NIT Warangal, India.

G. Sucharitha PhD from KL University, Vijayawada and is currently an assistant professor in the Department of Electronics and Communication Engineering at ICFAI Foundation for Higher Education Hyderabad.

Anjanna Matta PhD from the Indian Institute of Technology Hyderabad and is currently an assistant professor in the Department of Mathematics at ICFAI Foundation for Higher Education Hyderabad.

Prasenjit Chatterjee PhD is an associate professor in the Mechanical Engineering Department at MCKV Institute of Engineering, India.