Mastering Data Science
eBook - ePub

Mastering Data Science

Advanced Data Science

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Mastering Data Science

Advanced Data Science

About this book

Connect data questions with a more coherent analytical process

Mastering Data Science: Advanced Data Science brings your study of data science into focus. This Cybellium study guide connects data preparation, analysis and modelling and interpretation and communication, helping you see how the ideas fit together.

Develop a more connected understanding of the subject and the questions it raises. Use it to revisit the subject, connect its moving parts and identify the areas you want to study more deeply.

Build your understanding

  • Understand the role of data preparation.
  • Explore the relationships behind analysis and modelling.
  • Examine the choices and questions involving interpretation and communication.
  • Bring individual concepts together into a more coherent understanding of the subject.

Who this guide is for

For readers building on an existing foundation with an interest in data science. Use the book for focused study, revision or the next stage of your professional learning, returning to the ideas most relevant to your goals.

Your included Cybellium learning bonus

  • One complimentary month of Cybellium access.
  • One additional Cybellium guide download of your choice.
  • Access to the Cybellium Cybersecurity Knowledge Hub and premium learning resources during the included access period.

Activate your unique voucher at www.cybellium.com/signup to begin your included month and select your additional guide.

The included voucher is valid for one-time use only and cannot be combined with another offer.

Continue your learning with Mastering Data Science.

Information

Publisher
YouGuide
Year
2024
eBook ISBN
9798862563160

Table of contents

  1. Mastering Data Science
  2. 1. Introduction to Advanced Data Science
  3. 2. Mathematical and Statistical Foundations
  4. 3. Data Acquisition and Preparation
  5. 4. Exploratory Data Analysis (EDA)
  6. 5. Advanced Machine Learning Algorithms
  7. 6. Deep Learning and Neural Networks
  8. 7. Natural Language Processing (NLP)
  9. 8. Time Series Analysis and Forecasting
  10. 9. Big Data Technologies
  11. 10. Model Evaluation and Validation
  12. 11. Model Deployment and Operationalization
  13. 12. Data Science in Production Environments
  14. 13. Data Ethics and Responsible AI
  15. 14. Advanced Topics in Data Science
  16. 15. Collaboration and Teamwork in Data Science
  17. 16. Domain-Specific Applications
  18. 17. Challenges and Pitfalls in Advanced Data Science
  19. 18. Innovation and Future Trends
  20. 19. Practical Projects and Case Studies
  21. 20. Resources and Continuing Development

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