Online-Ressource
Verfasst von:	Voniatis, Andreas [VerfasserIn]
Titel:	Data-driven SEO with Python
Titelzusatz:	solve SEO challenges with data science using Python
Mitwirkende:	Critchlow, Will [MitwirkendeR]
Verf.angabe:	Andreas Voniatis ; foreword by Will Critchlow
Ausgabe:	[First edition].
Verlagsort:	New York, NY
Verlag:	Apress
E-Jahr:	2023
Jahr:	[2023]
Umfang:	1 online resource (xxvi, 580 pages)
Illustrationen:	illustrations (some color)
Fussnoten:	Includes index
ISBN:	978-1-4842-9175-7
	1-4842-9175-1
Abstract:	Solve SEO problems using data science. This hands-on book is packed with Python code and data science techniques to help you generate data-driven recommendations and automate the SEO workload. This book is a practical, modern introduction to data science in the SEO context using Python. With social media, mobile, changing search engine algorithms, and ever-increasing expectations of users for super web experiences, too much data is generated for an SEO professional to make sense of in spreadsheets. For any modern-day SEO professional to succeed, it is relevant to find an alternate solution, and data science equips SEOs to grasp the issue at hand and solve it. From machine learning to Natural Language Processing (NLP) techniques, Data-Driven SEO with Python provides tried and tested techniques with full explanations for solving both everyday and complex SEO problems. This book is ideal for SEO professionals who want to take their industry skills to the next level and enhance their business value, whether they are a new starter or highly experienced in SEO, Python programming, or both.
URL:	Aggregator: https://learning.oreilly.com/library/view/-/9781484291757/?ar
Datenträger:	Online-Ressource
Sprache:	eng
Bibliogr. Hinweis:	Erscheint auch als : Druck-Ausgabe
Sach-SW:	Python (Computer program language)
	Web search engines
K10plus-PPN:	1844460509
	Universitätsbibliothek
Lokale URL UB:	Zum Volltext
	Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
	Bestellen/Vormerken für Benutzer des Klinikums Mannheim Eigene Kennung erforderlich
Bibliothek/Idn:	UW / m4317561859
Lokale URL Inst.:	Zum Volltext