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Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning,New
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Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful.'Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI AdvantageYou've heard the hype around data now get the facts.In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, awardwinning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it.You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting dataBecoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities youll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Headan active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.
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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: How many pages does the book have? A: The book has two hundred seventy-two pages. This length provides a comprehensive overview of data science concepts.
- Q: What is the binding type of this book? A: The binding type is paperback. This makes it lightweight and easy to handle for reading.
- Q: What are the dimensions of the book? A: The book measures six inches wide, eight point nine inches tall, and zero point six inches thick. These dimensions make it portable and convenient for readers.
- Q: Who is the author of 'Becoming a Data Head'? A: The authors are Alex Gutman and Jordan Goldmeier. Both are award-winning data scientists with extensive experience in the field.
- Q: What is the main focus of this book? A: The main focus is to educate readers about data science, statistics, and machine learning. It aims to make complex topics accessible and understandable.
- Q: Is this book suitable for beginners in data science? A: Yes, the book is suitable for beginners. It provides foundational knowledge and tools to start thinking critically about data.
- Q: How can I apply what I learn from this book? A: You can apply the concepts by using them in workplace scenarios. The book teaches how to ask the right questions and interpret data effectively.
- Q: Is there a specific audience for this book? A: Yes, it targets business professionals, engineers, executives, and aspiring data scientists. It's designed for anyone looking to improve their data literacy.
- Q: Does this book include practical examples? A: Yes, it includes practical examples to illustrate key concepts. This helps readers relate the material to real-world situations.
- Q: What is the best way to keep this book in good condition? A: To keep it in good condition, store it in a dry place and avoid exposing it to direct sunlight. This will help preserve its quality.
- Q: Can I return the book if I am not satisfied? A: Yes, you can return the book if you are not satisfied, usually within a specified return window. Check the retailer's return policy for details.
- Q: Is there a warranty or guarantee for this book? A: No, there is typically no warranty for books. However, most retailers offer return policies for unsatisfied customers.
- Q: What should I do if the book arrives damaged? A: If the book arrives damaged, contact the seller for a replacement or refund. Most sellers have procedures for handling such issues.
- Q: Are there any prerequisites for reading this book? A: No, there are no prerequisites for reading this book. It is designed to be accessible to readers with various backgrounds.
- Q: Does the book cover advanced data science topics? A: Yes, it covers some advanced topics such as machine learning and deep learning. However, it presents them in an approachable manner.
- Q: What makes this book different from other data science books? A: This book focuses on making data science concepts relatable and understandable. It combines theory with practical advice tailored for the workplace.