𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Data science for business

✍ Scribed by Fawcett, Tom;Provost, Foster


Publisher
O'Reilly
Year
2013
Tongue
English
Leaves
414
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Subjects


Big data;Business--Data processing;Computación;Data mining;Information science;Minería de datos;Negocios--Procesamiento de datos;Business -- Data processing;Minería de datos;Computación;Negocios -- Procesamiento de datos


πŸ“œ SIMILAR VOLUMES


Data Science for Business
✍ Fawcett, Tom;Provost, Foster πŸ“‚ Library πŸ“… 2013 πŸ› O'Reilly Media 🌐 English

<p>Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This

Business Analytics: Data Science for Bus
✍ Walter R. Paczkowski πŸ“‚ Library πŸ“… 2022 πŸ› Springer 🌐 English

<p>This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of:</p> <p>1. statistical, econometric, and machine learning techniques;<br></p> <p>2. data handling capabilities;</p> <p>3. at lea

Data Science for Business With R
✍ Jeffrey S. Saltz, Jeffrey Morgan Stanton πŸ“‚ Library πŸ“… 2021 πŸ› SAGE Publications 🌐 English

<p><em>Data Science for Business with R, </em>written by Jeffrey S. Saltz and Jeffrey M. Stanton,<em> </em>focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using

Data Science for Business With R
✍ Jeffrey S. Saltz, Jeffrey Morgan Stanton πŸ“‚ Library πŸ“… 2021 πŸ› SAGE Publications 🌐 English

<p><em>Data Science for Business with R, </em>written by Jeffrey S. Saltz and Jeffrey M. Stanton,<em> </em>focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using

Data Science for Business and Decision M
✍ Luiz Paulo FΓ‘vero, PatrΓ­cia Belfiore πŸ“‚ Library πŸ“… 2019 πŸ› Academic Press 🌐 English

<p><i>Data Science for Business and Decision Making</i> covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their w

Applied Data Science: Lessons Learned fo
✍ Martin Braschler, Thilo Stadelmann, Kurt Stockinger πŸ“‚ Library πŸ“… 2019 πŸ› Springer International Publishing 🌐 English

<p><p></p><p>This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As s