Regular price €198.40
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Reza Shahbazian
A01=Seyedeh Leili Mirtaheri
Artifical Intelligence
Artificial Data sets
Author_Reza Shahbazian
Author_Seyedeh Leili Mirtaheri
Autonomous vehicles
Category=UYQM
Cognitive AI-based decision making
communication systems analysis
computational intelligence
Convolution Layer
Convolutional Layers
Convolutional netoworks
Cost Function
Dataset
DBNs
Deep Learning
deep learning evaluation tools
Dl Algorithm
DNN
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Generative Networks
Gradient Descent
Hidden Layer
Input Volume
KNN Classifier
L2 Regularization
Long Short term memory
Machine Learning
Ml Algorithm
Neural Network
neural network models
NVIDIA CUDA
Pooling Layer
Python programming for data science
Recurrent Nural networks
Reinforcement Learning Algorithms
RNNs
security in machine learning
signal processing techniques
Stochastic Gradient Descent
SVM Classifier
Synthetic data
Train Dataset
Training Dataset
Unsupervised Machine Learning
Validation Dataset

Product details

  • ISBN 9780367634537
  • Weight: 720g
  • Dimensions: 156 x 234mm
  • Publication Date: 29 Sep 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

The book reviews core concepts of machine learning (ML) while focusing on modern applications. It is aimed at those who want to advance their understanding of ML by providing technical and practical insights. It does not use complicated mathematics to explain how to benefit from ML algorithms. Unlike the existing literature, this work provides the core concepts with emphasis on fresh ideas and real application scenarios. It starts with the basic concepts of ML and extends the concepts to the different deep learning algorithms. The book provides an introduction and main elements of evaluation tools with Python and walks you through the recent applications of ML in self-driving cars, cognitive decision making, communication networks, security, and signal processing. The concept of generative networks is also presented and focuses on GANs as a tool to improve the performance of existing algorithms.

In summary, this book provides a comprehensive technological path from fundamental theories to the categorization of existing algorithms, covers state-of-the-art, practical evaluation tools and methods to empower you to use synthetic data to improve the performance of applications.

Seyedeh Leili Mirtaheri is an assistant professor in the Electrical and Computer Engineering Department at Kharazmi University. She holds PhD degrees in computer engineering and also in operations research. She has authored several journal articles and conference proceedings and has also been an author/editor of several books. She has been a guest editor of the Journal of Supercomputing and also the reviewer of many credible journals.

Reza Shahbazian is an assistant professor of Standard Research Institute (Iran) and researcher at Unical. He holds PhD degrees in telecommunications and computer science. He has served as a postdoc researcher on applications of machine learning in telecommunication networks. He has authored several articles in journals and conference proceedings, book chapters and also authored or edited five books.

More from this author