Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy, bìa mềm
-Machine Learning Theory and Applications-
Enables
readers to understand mathematical concepts behind data engineering and
machine learning algorithms and apply them using open-source Python
libraries
Machine Learning Theory and Applications delves into
the realm of machine learning and deep learning, exploring their
practical applications by comprehending mathematical concepts and
implementing them in real-world scenarios using Python and renowned
open-source libraries. This comprehensive guide covers a wide range of
topics, including data preparation, feature engineering techniques,
commonly utilized machine learning algorithms like support vector
machines and neural networks, as well as generative AI and foundation
models. To facilitate the creation of machine learning pipelines, a
dedicated open-source framework named hephAIstos has been developed
exclusively for this book. Moreover, the text explores the fascinating
domain of quantum machine learning and offers insights on executing
machine learning applications across diverse hardware technologies such
as CPUs, GPUs, and QPUs. Finally, the book explains how to deploy
trained models through containerized applications using Kubernetes and
OpenShift, as well as their integration through machine learning
operations (MLOps).
Additional topics covered in Machine Learning Theory and Applications include
Current
use cases of AI, including making predictions, recognizing images and
speech, performing medical diagnoses, creating intelligent supply
chains, natural language processing, and much more
Classical
and quantum machine learning algorithms such as quantum-enhanced Support
Vector Machines (QSVMs), QSVM multiclass classification, quantum neural
networks, and quantum generative adversarial networks (qGANs)
Different ways to manipulate data, such as handling missing data, analyzing categorical data, or processing time-related data
Feature rescaling, extraction, and selection, and how to put your trained models to
…
Categories:Computers - Artificial Intelligence (AI)
Content Type:Books
Year:2024
Edition:1
Language:english
Pages:510
