Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python

Author:   Sam Lau ,  Joseph Gonzalez ,  Deborah Nolan
Publisher:   O'Reilly Media
ISBN:  

9781098113001


Pages:   600
Publication Date:   30 September 2023
Format:   Paperback
Availability:   In Print   Availability explained
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Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python


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Author:   Sam Lau ,  Joseph Gonzalez ,  Deborah Nolan
Publisher:   O'Reilly Media
Imprint:   O'Reilly Media
ISBN:  

9781098113001


ISBN 10:   1098113004
Pages:   600
Publication Date:   30 September 2023
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Sam Lau is a PhD candidate at UC San Diego. He designs novel interfaces for learning and teaching data science, and his research has been published in top-tier conferences in human-computer interaction and end-user programming. Sam instructed and helped design flagship data science courses at UC Berkeley. These courses have grown to serve thousands of students every year and their curriculum is used by universities across the world. Joseph (Joey) Gonzalez is an assistant professor in the EECS department at UC Berkeley and a founding member of the new UC Berkeley RISE Lab. His research interests are at the intersection of machine learning and data systems, including: dynamic deep neural networks for transfer learning, accelerated deep learning for high-resolution computer vision, and software platforms for autonomous vehicles. Joey is also co-founder of Turi Inc. (formerly GraphLab), which was based on his work on the GraphLab and PowerGraph Systems. Turi was recently acquired by Apple Inc. Deborah (Deb) Nolan is Professor of Statistics and Associate Dean for Undergraduate Studies in the Division of Computing, Data Science, and Society at the University of California, Berkeley, where she holds the Zaffaroni Family Chair in Undergraduate Education. Her research has involved the empirical process, high-dimensional modeling, and, more recently, technology in education and reproducible research. Her pedagogical approach connects research, practice and education, and she is co-author of 4 textbooks: Stat Labs, Teaching Statistics, Data Science in R, and Communicating with Data.

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