Data-Driven SEO with Python Solve SEO Challenges with Data Science Using Python

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...

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Detalles Bibliográficos
Otros Autores: Voniatis, Andreas, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berkeley, CA : Apress 2023.
Edición:1st ed. 2023.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009729738106719
Descripción
Sumario: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. You will: See how data science works in the SEO context Think about SEO challenges in a data driven way Apply the range of data science techniques to solve SEO issues Understand site migration and relaunches .
Notas:Includes index.
Descripción Física:1 online resource (596 pages)
ISBN:9781484291757