Title
Humancentered Data Science: An Introduction-new
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Best Practices For Addressing The Bias And Inequality That May Result From The Automated Collection, Analysis, And Distribution Of Large Datasets.Humancentered Data Science Is A New Interdisciplinary Field That Draws From Humancomputer Interaction, Social Science, Statistics, And Computational Techniques. This Book, Written By Founders Of The Field, Introduces Best Practices For Addressing The Bias And Inequality That May Result From The Automated Collection, Analysis, And Distribution Of Very Large Datasets. It Offers A Brief And Accessible Overview Of Many Common Statistical And Algorithmic Data Science Techniques, Explains Humancentered Approaches To Data Science Problems, And Presents Practical Guidelines And Realworld Case Studies To Help Readers Apply These Methods.The Authors Explain How Data Scientists
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- Q: What is the page count of this book? A: This book has two hundred pages. It provides a comprehensive introduction to human-centered data science and its best practices.
- Q: What are the dimensions of the book? A: The book measures seven point zero one inches in length, zero point four nine inches in width, and ten inches in height. These dimensions make it portable and easy to handle.
- Q: What type of binding does this book have? A: The book is paperback bound. This makes it lightweight and flexible for easy reading.
- Q: Who is the author of this book? A: The author of this book is Cecilia Aragon. She is one of the founders of the field of human-centered data science.
- Q: What is the main focus of the book? A: The main focus of the book is on human-centered approaches to data science. It addresses issues of bias and inequality in data practices.
- Q: What audience is this book suitable for? A: This book is suitable for both beginners and experienced data scientists. It introduces concepts that are accessible and applicable across various levels of expertise.
- Q: How can I apply the concepts from this book? A: You can apply the concepts by following the practical guidelines and real-world case studies presented. The book encourages readers to incorporate human-centered techniques into their data science workflows.
- Q: Is this book appropriate for academic use? A: Yes, this book is appropriate for academic use. It provides a thorough overview of human-computer interaction and social science as they relate to data science.
- Q: What topics does the book cover? A: The book covers topics such as bias in data collection, algorithmic transparency, and data storytelling. It merges statistical techniques with ethical considerations.
- Q: How should I care for this book? A: To care for this book, keep it in a dry place and avoid exposure to direct sunlight. This will help maintain its condition.
- Q: What if the book arrives damaged? A: If the book arrives damaged, you should contact the seller for a return or exchange. Most sellers will have a return policy in place for such cases.
- Q: Can I return the book if I don't like it? A: Yes, you can return the book if you are unsatisfied, following the seller's return policy. Be sure to check the specific terms upon purchase.
- Q: Does this book provide case studies? A: Yes, the book includes real-world case studies. These examples illustrate the application of human-centered data science principles.
- Q: Is this book suitable for professionals in the field? A: Yes, this book is suitable for professionals. It offers insights that can enhance their existing data practices and address ethical concerns.
- Q: What is the publishing company for this book? A: The book is published by The MIT Press. They are known for their scholarly publications in various fields.
- Q: Are there any features included in the book? A: The book does not list specific features. However, it emphasizes best practices and human-centered approaches in data science.