[PDF] Analytical Skills For Ai And Data Science eBook

Author : Daniel Vaughan
Publisher : "O'Reilly Media, Inc."
Page : 300 pages
File Size : 17,97 MB
Release : 2020-05-21
Category : Computers
ISBN : 1492060895

GET BOOK

While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested end-to-end method to help you translate business decisions into tractable prescriptive solutions using data and AI as fundamental inputs. Author Daniel Vaughan shows data scientists, analytics practitioners, and others interested in using AI to transform their businesses not only how to ask the right questions but also how to generate value using modern AI technologies and decision-making principles. You’ll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. Break business decisions into stages that can be tackled using different skills from the analytical toolbox Identify and embrace uncertainty in decision making and protect against common human biases Customize optimal decisions to different customers using predictive and prescriptive methods and technologies Ask business questions that create high value through AI- and data-driven technologies

Author : Daniel Vaughan
Publisher : O'Reilly Media
Page : 250 pages
File Size : 20,8 MB
Release : 2020-08-11
Category : Computers
ISBN : 9781492060949

GET BOOK

While several market-leading companies have successfully transformed through data- and AI-driven approaches to business, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the potential of this predictive revolution? This practical guide presents a battle-tested method to help you translate business decisions into tractable descriptive, predictive, and prescriptive problems. Author Daniel Vaughan shows practitioners of data science and others interested in using AI not only how to ask the right questions but also how to generate value from data and analytics using modern AI technologies and decision theory principles. You'll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. With this book, you'll learn how to: Break business decisions into stages and use predictive or prescriptive methods on each stage Identify human biases when working with uncertainty Customize optimal decisions to different customers using predictive and prescriptive methods Ask business questions with high potential for value creation through AI and data-driven methods Simplify complexity to tackle difficult business decisions with current predictive and prescriptive technologies

Author : Eric Anderson
Publisher : McGraw Hill Professional
Page : 353 pages
File Size : 20,83 MB
Release : 2020-11-23
Category : Business & Economics
ISBN : 1260459152

GET BOOK

Lead your organization to become evidence-driven Data. It’s the benchmark that informs corporate projections, decision-making, and analysis. But, why do many organizations that see themselves as data-driven fail to thrive? In Leading with AI and Analytics, two renowned experts from the Kellogg School of Management show business leaders how to transform their organization to become evidence-driven, which leads to real, measurable changes that can help propel their companies to the top of their industries. The availability of unprecedented technology-enabled tools has made AI (Artificial Intelligence) an essential component of business analytics. But what’s often lacking are the leadership skills to integrate these technologies to achieve maximum value. Here, the authors provide a comprehensive game plan for developing that all-important human factor to get at the heart of data science: the ability to apply analytical thinking to real-world problems. Each of these tools and techniques comes to powerful life through a wealth of powerful case studies and real-world success stories. Inside, you’ll find the essential tools to help you: Develop a strong data science intuition quotient Lead and scale AI and analytics throughout your organization Move from “best-guess” decision making to evidence-based decisions Craft strategies and tactics to create real impact Written for anyone in a leadership or management role—from C-level/unit team managers to rising talent—this powerful, hands-on guide meets today’s growing need for real-world tools to lead and succeed with data.

Author : Foster Provost
Publisher : "O'Reilly Media, Inc."
Page : 506 pages
File Size : 48,88 MB
Release : 2013-07-27
Category : Computers
ISBN : 144937428X

GET BOOK

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

Author : Vincent Granville
Publisher : John Wiley & Sons
Page : 336 pages
File Size : 11,67 MB
Release : 2014-03-24
Category : Computers
ISBN : 1118810090

GET BOOK

Learn what it takes to succeed in the the most in-demand tech job Harvard Business Review calls it the sexiest tech job of the 21st century. Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT professionals. Data science involves extracting, creating, and processing data to turn it into business value. With over 15 years of big data, predictive modeling, and business analytics experience, author Vincent Granville is no stranger to data science. In this one-of-a-kind guide, he provides insight into the essential data science skills, such as statistics and visualization techniques, and covers everything from analytical recipes and data science tricks to common job interview questions, sample resumes, and source code. The applications are endless and varied: automatically detecting spam and plagiarism, optimizing bid prices in keyword advertising, identifying new molecules to fight cancer, assessing the risk of meteorite impact. Complete with case studies, this book is a must, whether you're looking to become a data scientist or to hire one. Explains the finer points of data science, the required skills, and how to acquire them, including analytical recipes, standard rules, source code, and a dictionary of terms Shows what companies are looking for and how the growing importance of big data has increased the demand for data scientists Features job interview questions, sample resumes, salary surveys, and examples of job ads Case studies explore how data science is used on Wall Street, in botnet detection, for online advertising, and in many other business-critical situations Developing Analytic Talent: Becoming a Data Scientist is essential reading for those aspiring to this hot career choice and for employers seeking the best candidates.

Author : Rayan Wali
Publisher : Rayan Wali
Page : 605 pages
File Size : 28,27 MB
Release : 2021-06-12
Category : Computers
ISBN :

GET BOOK

Whether you are looking to prepare for AI/ML/Data Science job interviews or you are a beginner in the field of Data Science and AI, this book is designed for engineers and AI enthusiasts like you at all skill levels. Taking a different approach from a traditional textbook style of instruction, A Practical Guide to AI and Data Analytics touches on all of the fundamental topics you will need to understand deeper into machine learning and artificial intelligence research, literature, and practical applications with its four parts: Part I: Concept Instruction Part II: 8 Full-Length Case Studies Part III: 50+ Mixed Exercises Part IV: A Full-Length Assessment With an illustrative approach to instruction, worked examples, and case studies, this easy-to-understand book simplifies many of the AI and Data Analytics key concepts, leading to an improvement of AI/ML system design skills.

Author : Daniel Vaughan
Publisher : "O'Reilly Media, Inc."
Page : 244 pages
File Size : 49,29 MB
Release : 2023-11-01
Category : Computers
ISBN : 1098146433

GET BOOK

This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline—machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: Understand how data science creates value Deliver compelling narratives to sell your data science project Build a business case using unit economics principles Create new features for a ML model using storytelling Learn how to decompose KPIs Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).

Author : Daniel Vaughan
Publisher : "O'Reilly Media, Inc."
Page : 257 pages
File Size : 44,86 MB
Release : 2023-11
Category : Computers
ISBN : 1098146441

GET BOOK

This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline—machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: Understand how data science creates value Deliver compelling narratives to sell your data science project Build a business case using unit economics principles Create new features for a ML model using storytelling Learn how to decompose KPIs Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).

Author : Gilbert Eijkelenboom
Publisher :
Page : 166 pages
File Size : 32,21 MB
Release : 2020-09-29
Category :
ISBN : 9789090336985

GET BOOK

Your analytical skills are incredibly valuable. However, rational thinking alone isn't enough. Have you ever: Presented an idea, but then no one seemed to care? Explained your analysis, only to leave your colleague confused? Struggled to work with people who are less analytical and more emotional? ​ In such situations, people skills make the difference. And that's what this book focuses on: boosting your communication skills as an analytical thinker. ​ Research shows people skills are becoming increasingly important in the workplace, so start learning today. ​ Filled with academic insights, exercises, and stories, this book will change your career. What you will learn ​ Having fun and productive interactions, even with people who don't have an analytical personality Boost your confidence and increase your empathy Learn how to deal with small-talk you don't enjoy Advance your communication skills and build relationships (th)at work Become incredibly persuasive by avoiding the single mistake that almost everyone makes

Author : Daniel Vaughan
Publisher :
Page : 48 pages
File Size : 20,18 MB
Release : 2020
Category :
ISBN :

GET BOOK

While several market-leading companies have successfully transformed through data- and AI-driven approaches to business, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the potential of this predictive revolution? This practical guide presents a battle-tested method to help you translate business decisions into tractable descriptive, predictive, and prescriptive problems. Author Daniel Vaughan shows practitioners of data science and others interested in using AI not only how to ask the right questions but also how to generate value from data and analytics using modern AI technologies and decision theory principles. You'll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. With this book, you'll learn how to: Break business decisions into stages and use predictive or prescriptive methods on each stage Identify human biases when working with uncertainty Customize optimal decisions to different customers using predictive and prescriptive methods Ask business questions with high potential for value creation through AI and data-driven methods Simplify complexity to tackle difficult business decisions with current predictive and prescriptive technologies.