| Titre : |
Data mining with python : theory, application, and case studies |
| Type de document : |
document électronique |
| Auteurs : |
Di Wu, Auteur |
| Editeur : |
Boca Raton [Etats-Unis] : Chapman & Hall / CRC |
| Année de publication : |
2024 |
| Collection : |
The Python Series |
| Importance : |
1 fichier PDF |
| Présentation : |
ill. |
| ISBN/ISSN/EAN : |
978-1-03-259890-1 |
| Note générale : |
Mode d'accès : accès au texte intégral par :
- authentification après inscription à la plateforme EBSCOhost
ou
- adresse IP de l'École.
Index |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Python (Computer program language)
Data mining--Computer programs |
| Index. décimale : |
004.4 Logiciel. Programme |
| Résumé : |
Data is everywhere and it's growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: “What it is” as a theoretical background, “why we need it” as an application orientation, and “how we do it” as a case study.This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified, and used for a more comprehensive learning experience, this book will help its readers to gain practical skills to implement Data Mining techniques in their work. |
| Note de contenu : |
Summary of the book :
1. Data Wrangling
2. Data Analysis |
| En ligne : |
https://research.ebsco.com/linkprocessor/plink?id=c1b72c8e-db8f-3633-8aac-02d82b [...] |
Data mining with python : theory, application, and case studies [document électronique] / Di Wu, Auteur . - Boca Raton [Etats-Unis] : Chapman & Hall / CRC, 2024 . - 1 fichier PDF : ill.. - ( The Python Series) . ISBN : 978-1-03-259890-1 Mode d'accès : accès au texte intégral par :
- authentification après inscription à la plateforme EBSCOhost
ou
- adresse IP de l'École.
Index Langues : Anglais ( eng)
| Mots-clés : |
Python (Computer program language)
Data mining--Computer programs |
| Index. décimale : |
004.4 Logiciel. Programme |
| Résumé : |
Data is everywhere and it's growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: “What it is” as a theoretical background, “why we need it” as an application orientation, and “how we do it” as a case study.This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified, and used for a more comprehensive learning experience, this book will help its readers to gain practical skills to implement Data Mining techniques in their work. |
| Note de contenu : |
Summary of the book :
1. Data Wrangling
2. Data Analysis |
| En ligne : |
https://research.ebsco.com/linkprocessor/plink?id=c1b72c8e-db8f-3633-8aac-02d82b [...] |
|  |
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