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Data Science (The Mit Press Essential Knowledge Series),New
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A Concise Introduction To The Emerging Field Of Data Science, Explaining Its Evolution, Relation To Machine Learning, Current Uses, Data Infrastructure Issues, And Ethical Challenges.The Goal Of Data Science Is To Improve Decision Making Through The Analysis Of Data. Today Data Science Determines The Ads We See Online, The Books And Movies That Are Recommended To Us Online, Which Emails Are Filtered Into Our Spam Folders, And Even How Much We Pay For Health Insurance. This Volume In The Mit Press Essential Knowledge Series Offers A Concise Introduction To The Emerging Field Of Data Science, Explaining Its Evolution, Current Uses, Data Infrastructure Issues, And Ethical Challenges.It Has Never Been Easier For Organizations To Gather, Store, And Process Data. Use Of Data Science Is Driven By The Rise Of Big Data And Social Media, The Development Of Highperformance Computing, And The Emergence Of Such Powerful Methods For Data Analysis And Modeling As Deep Learning. Data Science Encompasses A Set Of Principles, Problem Definitions, Algorithms, And Processes For Extracting Nonobvious And Useful Patterns From Large Datasets. It Is Closely Related To The Fields Of Data Mining And Machine Learning, But Broader In Scope. This Book Offers A Brief History Of The Field, Introduces Fundamental Data Concepts, And Describes The Stages In A Data Science Project. It Considers Data Infrastructure And The Challenges Posed By Integrating Data From Multiple Sources, Introduces The Basics Of Machine Learning, And Discusses How To Link Machine Learning Expertise With Realworld Problems. The Book Also Reviews Ethical And Legal Issues, Developments In Data Regulation, And Computational Approaches To Preserving Privacy. Finally, It Considers The Future Impact Of Data Science And Offers Principles For Success In Data Science Projects.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the page count of this book? A: This book has two hundred eighty pages. It provides a comprehensive overview of data science principles and applications.
- Q: What are the dimensions of this book? A: The book measures five inches in length, zero point seventy-nine inches in width, and seven point zero one inches in height. This makes it a compact and portable read.
- Q: What type of binding does this book have? A: This book is available in paperback binding. This allows for easy handling and reading.
- Q: Who is the author of this book? A: The author of this book is John D. Kelleher. He offers insights based on his expertise in data science.
- Q: What category does this book fall under? A: This book falls under the Data Processing category. It focuses on essential knowledge in the field of data science.
- Q: What topics does this book cover? A: This book covers topics such as data science evolution, machine learning, data infrastructure, and ethical challenges. It provides a well-rounded introduction to the field.
- Q: Who would benefit from reading this book? A: This book is suitable for beginners and professionals interested in data science. It offers valuable insights for anyone looking to understand the field.
- Q: Is this book suitable for someone new to data science? A: Yes, this book is suitable for beginners. It offers a concise introduction to fundamental concepts in data science.
- Q: What skills can I gain from this book? A: You can gain foundational knowledge in data analysis, machine learning basics, and ethical considerations in data science. It prepares you for real-world applications.
- Q: How should I care for this book? A: To care for this book, keep it in a dry place and avoid exposing it to direct sunlight. This will help maintain its condition.
- Q: Is there a specific way to store this book? A: Yes, storing this book upright on a shelf is recommended. This helps prevent bending or damage to the spine.
- Q: Can I return this book if I am not satisfied? A: Yes, you can return this book if you are not satisfied. Please check the return policy for specific details.
- Q: What if the book arrives damaged? A: If the book arrives damaged, you should contact customer support immediately. They can assist you in processing a return or exchange.
- Q: Is there a warranty for this book? A: No, there is typically no warranty for books. However, customer support can help with issues related to your purchase.
- Q: How do I contact support if I have an issue? A: You can contact customer support through the retailer’s website or customer service number. They will assist you with any issues.
- Q: What makes this book different from other data science books? A: This book stands out due to its concise overview of both foundational and contemporary issues in data science. It combines historical context with practical applications.