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Data Science The Hard Parts


Data Science The Hard Parts
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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

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 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 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).



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



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).



R For Data Science


R For Data Science
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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-12-12

R For Data Science written by Hadley Wickham 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 2016-12-12 with Computers categories.


Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results



Step Up For Leadership In Enterprise Data Science Artificial Intelligence With Big Data


Step Up For Leadership In Enterprise Data Science Artificial Intelligence With Big Data
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Author : Shitalkumar R Sukhdeve
language : en
Publisher: Independently Published
Release Date : 2020-11-27

Step Up For Leadership In Enterprise Data Science Artificial Intelligence With Big Data written by Shitalkumar R Sukhdeve and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-27 with categories.


Review: "I would recommend this book to all prospective data scientists - as well as those software professionals who choose to transfer or migrate to the domain of data science. It is a useful addition to the body of work already available to guide project managers of data science projects." Lt Col (Dr) Rajesh Kapur (Retd), AI Investor, Asst. Prof. TIMSCDR, Hyderabad, India "It's a masterpiece of work for the aspiring leaders of data science and AI. It's also a guide for executives and investors to get maximum value from their investment in AI. Beginners in data science can also get the most out of this book.", Jay Ojha, Business intelligence and analytics manager, HCL Infosystem LtdWhy should you read this book? 87% of data science project fails to make to production in enterprises. Only 50% is the data leadership success rate. Is it not surprising to know when data science and AI are in the top trend? If you are looking for a career in data science or looking for leadership, these insights may disturb you. Don't worry, "Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data." will -Burst the myths around data science, AI & big data-Presents the real business scenarios -Take you on the journey of data science, AI & big data even if you are an ultimate beginner.-Introduce you to the essential skills of success in this field -Develop a leadership mindset by cutting edge methodologies & strategies-Make you aware of technical trends around it-Develop technical skills with R, Python, Machine learning with big data as well as business skills-Reduce failure possibility and increase the chance of success by covering the 360 degrees view of the field. Each day counts. So as your steps. Step up immediately and begin your journey to your dreams of data science and AI.



Data Science


Data Science
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Author : Qurban A Memon
language : en
Publisher: CRC Press
Release Date : 2019-09-26

Data Science written by Qurban A Memon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-26 with Computers categories.


The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on challenging topics in the area surrounding data science. In this book, some of the chapters are written in tutorial style concerning machine learning algorithms, data analysis, information design, infographics, relevant applications, etc. The book is structured as follows: • Part I: Data Science: Theory, Concepts, and Algorithms This part comprises five chapters on data Science theory, concepts, techniques and algorithms. • Part II: Data Design and Analysis This part comprises five chapters on data design and analysis. • Part III: Applications and New Trends in Data Science This part comprises four chapters on applications and new trends in data science.



Data Science For Dummies


Data Science For Dummies
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Author : Lillian Pierson
language : en
Publisher: John Wiley & Sons
Release Date : 2021-09-15

Data Science For Dummies written by Lillian Pierson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-15 with Computers categories.


Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today.



Data Science For Beginners


Data Science For Beginners
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Author : Prof John Smith
language : en
Publisher: Independently Published
Release Date : 2018-12-12

Data Science For Beginners written by Prof John Smith and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with categories.


DATA SCIENCE FOR BEGINNERS Introduction to Data Science: Python,Coding, Application, Statistics,Decision Tree, Neural Network, and Linear Algebra WHAT THIS BOOK WILL DO FOR YOU We will talk about what is the need for data science and then what exactly is data science some definitions and understand. The differences between data science and business intelligence,Then we will talk about the prerequisites for learning data science, and then what does the data scientist do. What are the activities performed by a data scientist as a part of his daily life and then we will talk about the data science lifecycle witha quick example and briefly touch upon the demand or ever-increasing demand for data scientist. Benefits of Data science Data Science: Automobile Data science: Aviation Data science can also be used to make promotional offers. Chapters Data science: Its Advantage Data science: Its Definition Process in data science Difference between business intelligence and data science Prerequisites for data science Machine learning. Data science: Tools and skills in data science. Data Science: Machine-learning algorithms Data science: Life cycle of a data science Data science: Exploratory data analysis Data science: Techniques for exploratory data analysis



Data Science


Data Science
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Author : Vijay Kotu
language : en
Publisher: Morgan Kaufmann
Release Date : 2018-11-27

Data Science written by Vijay Kotu and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-27 with Computers categories.


Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You’ll be able to: Gain the necessary knowledge of different data science techniques to extract value from data. Master the concepts and inner workings of 30 commonly used powerful data science algorithms. Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naïve Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more... Contains fully updated content on data science, including tactics on how to mine business data for information Presents simple explanations for over twenty powerful data science techniques Enables the practical use of data science algorithms without the need for programming Demonstrates processes with practical use cases Introduces each algorithm or technique and explains the workings of a data science algorithm in plain language Describes the commonly used setup options for the open source tool RapidMiner