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Can I read 15 Math Concepts Every Data Scientist Should Know : Understand and Learn How to Apply the Math Behind Data Science Algorithms on EtoBox?
15 Math Concepts Every Data Scientist Should Know : Understand and Learn How to Apply the Math Behind Data Science Algorithms by David Hoyle is a nonfiction available to read on EtoBox.
What is 15 Math Concepts Every Data Scientist Should Know : Understand and Learn How to Apply the Math Behind Data Science Algorithms about?
Create more effective and powerful data science solutions by learning when, where, and how to apply key math principles that drive most data science algorithmsKey FeaturesUnderstand key data science algorithms with Python-based examplesIncrease the impact of your data science solutions by learning how to apply existing algorithmsTake your data science solutions to the next level by learning how to create new algorithmsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionData science combines the power of data with the rigor of scientific methodology, with mathematics providing the tools and frameworks for analysis, algorithm development, and deriving insights. As machine learning algorithms become increasingly complex, a solid grounding in math is crucial for data scientists. David Hoyle, with over 30 years of experience in statistical and mathematical modeling, brings unparalleled industrial expertise to this book, drawing from his work in building predictive models for the world's largest retailers. Encompassing 15 crucial concepts, this book covers a spectrum of mathematical techniques to help you understand a vast range of data science algorithms and ap
Who reads 15 Math Concepts Every Data Scientist Should Know : Understand and Learn How to Apply the Math Behind Data Science Algorithms?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- David Hoyle
- Publisher
- Packt Publishing - ebooks Account
- Published
- 2024
- Language
- EN
- ISBN
- 9783319708850
- Category
- nonfiction
- Subjects
- Science, Mathematics, Computer Science
Other editions & translations
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