Analytical Skills For Ai And Data Science


Analytical Skills For Ai And Data Science
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Analytical Skills For Ai And Data Science


Analytical Skills For Ai And Data Science
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Author : Daniel Vaughan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-05-21

Analytical Skills For Ai And Data Science written by Daniel Vaughan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-21 with Computers categories.


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



Analytical Skills For Ai And Data Science


Analytical Skills For Ai And Data Science
DOWNLOAD eBooks

Author : Daniel Vaughan
language : en
Publisher: O'Reilly Media
Release Date : 2020-05-21

Analytical Skills For Ai And Data Science written by Daniel Vaughan and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-21 with Computers categories.


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



Leading With Ai And Analytics Build Your Data Science Iq To Drive Business Value


Leading With Ai And Analytics Build Your Data Science Iq To Drive Business Value
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Author : Eric Anderson
language : en
Publisher: McGraw Hill Professional
Release Date : 2020-11-23

Leading With Ai And Analytics Build Your Data Science Iq To Drive Business Value written by Eric Anderson and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Business & Economics categories.


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.



A Practical Guide To Artificial Intelligence And Data Analytics


A Practical Guide To Artificial Intelligence And Data Analytics
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Author : Rayan Wali
language : en
Publisher: Rayan Wali
Release Date : 2021-06-12

A Practical Guide To Artificial Intelligence And Data Analytics written by Rayan Wali and has been published by Rayan Wali this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-12 with Computers categories.


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.



Data Science The Hard Parts


Data Science The Hard Parts
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Author : Daniel Vaughan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-11-01

Data Science The Hard Parts written by Daniel Vaughan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-01 with Computers categories.


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).



A Practical Guide To Ai And Data Analytics


A Practical Guide To Ai And Data Analytics
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Author : Rayan Wali
language : en
Publisher:
Release Date : 2022-01-05

A Practical Guide To Ai And Data Analytics written by Rayan Wali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-05 with categories.


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 three parts: Part I: A Conceptual (and Visual) Illustration [topics including, but not limited to, are listed below] Fundamentals of Data Science The Data and Machine Learning Pipelines Data Preprocessing + Worked Data Preprocessing Strategy Data Visualization Python for Data Analysis Calculus & Linear Algebra Fundamentals Data Structures and Algorithms Exercises Machine Learning Models & Algorithms (kNN, Neural Networks, Hidden Markov Models, Ensemble Methods, etc.) Deep Learning for Computer Vision & NLP (CNNs, RNNs, etc.) Data Mining Model Deployment Time Series Data Analysis AI Systems in the Real-World Applications of Data Analysis Exercises Database Systems & Cloud Computing (with practical example) Functional Programming for Data Analytics Part II: 10 Full-Length Case Studies Case Study I: Sports Web Scraping Case Study II: NLP Textual Analysis Case Study III: Emergency Response Duration Analysis Case Study IV: MNIST Image Classification Case Study V: COVID-19 Statistical Data Analysis Case Study VI: COVID-19 Chest X-Ray Screening Case Study VII: Signal Strength Geospatial Analysis Case Study VIII: NYC Crash Accidents Data Analysis Case Study IX: Sales Forecasting Case Study X: Meteorite Landings Analysis Part III: A Full-Length Data Science and Analytics Skills Assessment (DSSA) With exercises that span a wide range of AI problems from different domains, from the economics and finance to transportation and medical industries, the DSSA aims to provide a comprehensive assessment to measure your understanding through cleverly-designed AI reasoning, problem-solving, and scenario-based exercises, whether you use it to enhance your understanding in the AI and Data Analytics field or use it to prepare for your AI/Data Analytics problem solving and system design interviews. Section I: 60 Multiple-Choice and Short-Answer Exercises Section II: 5 AI & Data Analytics Problem Solving and Coding Exercises Solutions to Sections I and II are included 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.



Data Science For Business


Data Science For Business
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Author : Foster Provost
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-07-27

Data Science For Business written by Foster Provost and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-27 with Computers categories.


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



Data Science The Hard Parts Techniques For Excelling At Data Science


Data Science The Hard Parts Techniques For Excelling At Data Science
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Author : Daniel Vaughan
language : en
Publisher: O'Reilly Media
Release Date : 2024-03-05

Data Science The Hard Parts Techniques For Excelling At Data Science written by Daniel Vaughan and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-05 with Computers categories.


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).



Data Science Thinking


Data Science Thinking
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Author : Longbing Cao
language : en
Publisher: Springer
Release Date : 2018-08-17

Data Science Thinking written by Longbing Cao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-17 with Computers categories.


This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.



Data Science For Beginners


Data Science For Beginners
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Author : Andrew Park
language : en
Publisher:
Release Date : 2021-02-09

Data Science For Beginners written by Andrew Park and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-09 with categories.


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