Téléchargez le livre : Practical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python

de

Éditeur :

Academic Press


Paru le : 2020-06-05

eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈 ebook sans DRM
Lecture en ligne (streaming)
114,99 €
Téléchargement immédiat
Dès validation de votre commande
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

badge apple Application Louise Reader
badge Android Application Louise Reader
Description
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. - Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas - Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data - Explores important classification and regression algorithms as well as other machine learning techniques - Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features
Pages
534 pages
Collection
n.c
Parution
2020-06-05
Marque
Academic Press
EAN papier
9780128213797
EAN PDF
9780128213803
Informations sur l'ebook
Nombre pages copiables
53
Nombre pages imprimables
53
Taille du fichier
9574 Ko
Prix
114,99 €
EAN EPUB SANS DRM
9780128213803
Informations sur l'ebook
Prix
114,99 €

Suggestions personnalisées