Data-Driven SEO with Python
eBook - ePub

Data-Driven SEO with Python

Solve SEO Challenges with Data Science Using Python

  1. English
  2. ePUB (mobile friendly)
  3. Only available on web
eBook - ePub

Data-Driven SEO with Python

Solve SEO Challenges with Data Science Using Python

Book details
Table of contents
Citations

About This Book

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.

What You'll Learn

  • 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 are

Who This Book Is For
SEO practitioners, either at the department head level or all the way to the new career starter looking to improve their skills. Readers should have basic knowledge of Python to perform tasks like querying an API with some data exploration and visualization.

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Yes, you can access Data-Driven SEO with Python by Andreas Voniatis in PDF and/or ePUB format, as well as other popular books in Mathematics & Optimization. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Apress
Year
2023
ISBN
9781484291757
Topic
Mathematics
Subtopic
Optimization
Index
Mathematics

Table of contents

  1. Cover
  2. Front Matter
  3. 1. Introduction
  4. 2. Keyword Research
  5. 3. Technical
  6. 4. Content and UX
  7. 5. Authority
  8. 6. Competitors
  9. 7. Experiments
  10. 8. Dashboards
  11. 9. Site Migration Planning
  12. 10. Google Updates
  13. 11. The Future of SEO
  14. Back Matter