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Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models
Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models

Explore and master the most important algorithms for solving complex machine learning problems.

Key Features

  • Discover high-performing machine learning algorithms and understand how they work in depth
  • One-stop solution to mastering supervised, unsupervised, and...
Satellite Image Analysis: Clustering and Classification (SpringerBriefs in Applied Sciences and Technology)
Satellite Image Analysis: Clustering and Classification (SpringerBriefs in Applied Sciences and Technology)
Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision...
Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python
Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python
The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks) dealing not only with images and the use of computers, but also their applications to visualization tasks...
Ansible Playbook Essentials
Ansible Playbook Essentials

Design automation blueprints using Ansible's playbooks to orchestrate and manage your multitier infrastructure

About This Book

  • Get to grips with Ansible's features such as orchestration, automatic node discovery, and data encryption
  • Create data-driven, modular and reusable...
Challenges in Social Network Research: Methods and Applications (Lecture Notes in Social Networks)
Challenges in Social Network Research: Methods and Applications (Lecture Notes in Social Networks)

The book includes both invited and contributed chapters dealing with advanced methods and theoretical development for the analysis of social networks and applications in numerous disciplines. Some authors explore new trends related to network measures, multilevel networks and clustering on networks, while other contributions deepen...

Pattern Recognition, Second Edition
Pattern Recognition, Second Edition
Pattern recognition is becoming increasingly important in the age of automation and information handling and retrieval.
This book provides the most comprehensive treatment available of pattern recognition, from an engineering perspective. Developed through more than ten years of teaching experience, Pattern Recognition is appropriate for both
...
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

Build, scale, and deploy deep neural network models using the star libraries in Python

Key Features

  • Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras
  • Build, deploy, and scale end-to-end deep neural network models in a production...
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems

Insightful projects to master deep learning and neural network architectures using Python and Keras

Key Features

  • Explore deep learning across computer vision, natural language processing (NLP), and image processing
  • Discover best practices for the training of deep neural...
Information Retrieval: Data Structures and Algorithms
Information Retrieval: Data Structures and Algorithms

Information retrieval is a sub-field of computer science that deals with the automated storage and retrieval of documents. Providing the latest information retrieval techniques, this guide discusses Information Retrieval data structures and algorithms, including implementations in C. Aimed at software engineers building systems with...

VMware Cookbook: A Real-World Guide to Effective VMware Use
VMware Cookbook: A Real-World Guide to Effective VMware Use

With scores of step-by-step solutions, this cookbook helps you work with VMware ESXi in a wide range of network environments. You’ll not only learn the basics—how to pool resources from hardware servers, computer clusters, networks, and storage, and then distribute them among virtual machines—but also how to...

Principles of Data Mining (Undergraduate Topics in Computer Science)
Principles of Data Mining (Undergraduate Topics in Computer Science)

Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas.

Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each...

Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition
Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition

Build a strong foundation of machine learning algorithms in 7 days

Key Features

  • Use Python and its wide array of machine learning libraries to build predictive models
  • Learn the basics of the 7 most widely used machine learning algorithms within a week
  • Know...
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