Automated Machine Learning (AutoML) for Zero - touch Network and Service Management
Date: 18 September 2026 | Posted by: BeMyLove
Automated Machine Learning (AutoML) for Zero - touch Network and Service Management | 72.4 MB
Title: Automated Machine Learning (AutoML) for Zero - touch Network and Service Management
Author: Prithi Samuel, Malathy Sathyamoorthy, Rajesh Kumar Dhanaraj, Balamurugan Balusamy
Category: Business Software, Data Processing, Expert Systems
Language: English | 436 Pages | ISBN: 9781800565524
Description:
Automate data and model pipelines for faster machine learning applications
Key Features
Build automated modules for different machine learning components
Understand each component of a machine learning pipeline in depth
Learn to use different open source AutoML and feature engineering platforms
Book Description
AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners' work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible.
In this book, you'll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning.
By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you'll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions.
What you will learn
Understand the fundamentals of Automated Machine Learning systems
Explore auto-sklearn and MLBox for AutoML tasks
Automate your preprocessing methods along with feature transformation
Enhance feature selection and generation using the Python stack
Assemble individual components of ML into a complete AutoML framework
Demystify hyperparameter tuning to optimize your ML models
Dive into Machine Learning concepts such as neural networks and autoencoders
Understand the information costs and trade-offs associated with AutoML
Who this book is for
If you're a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you. You'll also find this book useful if you're an ML engineer or data professional interested in developing quick machine learning pipelines for your projects. Prior exposure to Python programming will help you get the best out of this book.
Table of Contents
Introduction to AutoML
Introduction to Machine Learning Using Python
Data Preprocessing
Automated Algorithm Selection
Hyperparameter Optimization
Creating AutoML pipelines
Dive into Deep Learning
Critical Aspects of ML and Data Science Projects
DOWNLOAD:
https://rapidgator.net/file/fc87db5d173d77807c90719fbfd27242/Automated_Machine_Learning_AutoML_for_Zero-touch_Network_and_Service_Management.rar
https://nitroflare.com/view/F475FAECE039DC9/Automated_Machine_Learning_AutoML_for_Zero-touch_Network_and_Service_Management.rar
Automate data and model pipelines for faster machine learning applications
Key Features
Book Description
AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners' work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible.
In this book, you'll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning.
By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you'll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions.
What you will learn
Who this book is for
If you're a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you. You'll also find this book useful if you're an ML engineer or data professional interested in developing quick machine learning pipelines for your projects. Prior exposure to Python programming will help you get the best out of this book.
Table of Contents
DOWNLOAD:
https://rapidgator.net/file/fc87db5d173d77807c90719fbfd27242/Automated_Machine_Learning_AutoML_for_Zero-touch_Network_and_Service_Management.rar
https://nitroflare.com/view/F475FAECE039DC9/Automated_Machine_Learning_AutoML_for_Zero-touch_Network_and_Service_Management.rar
See full article