
Becoming a Data Head
How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
カートのアイテムが多すぎます
カートに追加できませんでした。
ウィッシュリストに追加できませんでした。
ほしい物リストの削除に失敗しました。
ポッドキャストのフォローに失敗しました
ポッドキャストのフォロー解除に失敗しました
Audibleプレミアムプラン30日間無料体験
¥6,000 で購入
-
ナレーター:
-
Brian Arens
このコンテンツについて
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 Advantage
You'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, award-winning 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 data
Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll 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 bingeable book. Anyone can become a Data Head—an 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.
This audiobook is skillfully read by Brian Arens and was produced and published by Echo Point Books & Media, an independent bookseller in Brattleboro, Vermont.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
©2021 Alex J. Gutman and Jordan Goldmeier (P)2024 Echo Point Books & Media, LLCこちらもおすすめ
-
Big Data in Practice
- How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results
- 著者: Bernard Marr
- ナレーター: Lyle Blaker
- 再生時間: 7 時間 1 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
From technology, media, and retail to sport teams, government agencies, and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety, and so much more. Organized for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved, and the processes put in place to make it practical, as well as the technical details, challenges, and lessons learned from each unique scenario.
著者: Bernard Marr
-
Fundamentals of Data Engineering
- Plan and Build Robust Data Systems
- 著者: Joe Reis, Matt Housley
- ナレーター: Adam Verner
- 再生時間: 17 時間 31 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.
著者: Joe Reis, 、その他
-
Data Science for Dummies
- 2nd Edition
- 著者: Lillian Pierson, Jake Porway - foreword
- ナレーター: Chloe Cannon
- 再生時間: 10 時間 28 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.
著者: Lillian Pierson, 、その他
-
Probably the Best Book on Statistics Ever Written
- How to Beat the Odds and Make Better Decisions
- 著者: Haim Shapira
- ナレーター: Qarie Marshall
- 再生時間: 9 時間 56 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
This book reveals how statistics and probability are fundamental to our everyday lives—from advertisements to public opinion polls, weather forecasts to government policies, scientific research to stock market information. Haim Shapira then presents a myriad of anecdotes, riddles, case studies and practical exercises in his trademark witty voice to guide the listner through the importance of statistics and probability in everyday life.
著者: Haim Shapira
-
Introducing Python (2nd Edition)
- Modern Computing in Simple Packages
- 著者: Bill Lubanovic
- ナレーター: Derek Dysart
- 再生時間: 13 時間 3 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
Easy to understand and engaging, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you've learned.
著者: Bill Lubanovic
-
The Decision Intelligence Handbook
- Practical Steps for Evidence-Based Decisions in a Complex World
- 著者: L. Y. Pratt, N.E. Malcolm
- ナレーター: Daniel Henning
- 再生時間: 10 時間 2 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
Decision intelligence (DI) has been widely named as a top technology trend for several years, and Gartner reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or data-driven decision strategies. But until now, there has been little practical guidance for organizations to formalize decision making and integrate their decisions with data. With this book, authors L. Y. Pratt and N. E. Malcolm fill this gap.
著者: L. Y. Pratt, 、その他
-
Big Data in Practice
- How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results
- 著者: Bernard Marr
- ナレーター: Lyle Blaker
- 再生時間: 7 時間 1 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
From technology, media, and retail to sport teams, government agencies, and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety, and so much more. Organized for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved, and the processes put in place to make it practical, as well as the technical details, challenges, and lessons learned from each unique scenario.
著者: Bernard Marr
-
Fundamentals of Data Engineering
- Plan and Build Robust Data Systems
- 著者: Joe Reis, Matt Housley
- ナレーター: Adam Verner
- 再生時間: 17 時間 31 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.
著者: Joe Reis, 、その他
-
Data Science for Dummies
- 2nd Edition
- 著者: Lillian Pierson, Jake Porway - foreword
- ナレーター: Chloe Cannon
- 再生時間: 10 時間 28 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.
著者: Lillian Pierson, 、その他
-
Probably the Best Book on Statistics Ever Written
- How to Beat the Odds and Make Better Decisions
- 著者: Haim Shapira
- ナレーター: Qarie Marshall
- 再生時間: 9 時間 56 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
This book reveals how statistics and probability are fundamental to our everyday lives—from advertisements to public opinion polls, weather forecasts to government policies, scientific research to stock market information. Haim Shapira then presents a myriad of anecdotes, riddles, case studies and practical exercises in his trademark witty voice to guide the listner through the importance of statistics and probability in everyday life.
著者: Haim Shapira
-
Introducing Python (2nd Edition)
- Modern Computing in Simple Packages
- 著者: Bill Lubanovic
- ナレーター: Derek Dysart
- 再生時間: 13 時間 3 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
Easy to understand and engaging, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you've learned.
著者: Bill Lubanovic
-
The Decision Intelligence Handbook
- Practical Steps for Evidence-Based Decisions in a Complex World
- 著者: L. Y. Pratt, N.E. Malcolm
- ナレーター: Daniel Henning
- 再生時間: 10 時間 2 分
- 完全版
-
総合評価
-
ナレーション
-
ストーリー
Decision intelligence (DI) has been widely named as a top technology trend for several years, and Gartner reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or data-driven decision strategies. But until now, there has been little practical guidance for organizations to formalize decision making and integrate their decisions with data. With this book, authors L. Y. Pratt and N. E. Malcolm fill this gap.
著者: L. Y. Pratt, 、その他