Data Training
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Training Data For Machine Learning
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Author : Anthony Sarkis
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-11-08
Training Data For Machine Learning written by Anthony Sarkis 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 2023-11-08 with Computers categories.
Your training data has as much to do with the success of your data project as the algorithms themselves because most failures in AI systems relate to training data. But while training data is the foundation for successful AI and machine learning, there are few comprehensive resources to help you ace the process. In this hands-on guide, author Anthony Sarkis--lead engineer for the Diffgram AI training data software--shows technical professionals, managers, and subject matter experts how to work with and scale training data, while illuminating the human side of supervising machines. Engineering leaders, data engineers, and data science professionals alike will gain a solid understanding of the concepts, tools, and processes they need to succeed with training data. With this book, you'll learn how to: Work effectively with training data including schemas, raw data, and annotations Transform your work, team, or organization to be more AI/ML data-centric Clearly explain training data concepts to other staff, team members, and stakeholders Design, deploy, and ship training data for production-grade AI applications Recognize and correct new training-data-based failure modes such as data bias Confidently use automation to more effectively create training data Successfully maintain, operate, and improve training data systems of record
Data Science Careers Training And Hiring
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Author : Renata Rawlings-Goss
language : en
Publisher: Springer
Release Date : 2019-08-02
Data Science Careers Training And Hiring written by Renata Rawlings-Goss and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-02 with Education categories.
This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data. The book is divided into three sections, the first “Building Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second “Building Data Programs” is from the perspective of a newly forming data science degree or training program, and the third “Building Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations. The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, who they want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build.
The Data Science Workshop
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Author : Anthony So
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-29
The Data Science Workshop written by Anthony So and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-29 with Computers categories.
Cut through the noise and get real results with a step-by-step approach to data science Key Features Ideal for the data science beginner who is getting started for the first time A data science tutorial with step-by-step exercises and activities that help build key skills Structured to let you progress at your own pace, on your own terms Use your physical print copy to redeem free access to the online interactive edition Book DescriptionYou already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You'll learn from real examples that lead to real results. Throughout The Data Science Workshop, you'll take an engaging step-by-step approach to understanding data science. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your data science book. Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. You'll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.What you will learn Find out the key differences between supervised and unsupervised learning Manipulate and analyze data using scikit-learn and pandas libraries Learn about different algorithms such as regression, classification, and clustering Discover advanced techniques to improve model ensembling and accuracy Speed up the process of creating new features with automated feature tool Simplify machine learning using open source Python packages Who this book is forOur goal at Packt is to help you be successful, in whatever it is you choose to do. The Data Science Workshop is an ideal data science tutorial for the data science beginner who is just getting started. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.
Training Students To Extract Value From Big Data
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2015-01-16
Training Students To Extract Value From Big Data written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-16 with Mathematics categories.
As the availability of high-throughput data-collection technologies, such as information-sensing mobile devices, remote sensing, internet log records, and wireless sensor networks has grown, science, engineering, and business have rapidly transitioned from striving to develop information from scant data to a situation in which the challenge is now that the amount of information exceeds a human's ability to examine, let alone absorb, it. Data sets are increasingly complex, and this potentially increases the problems associated with such concerns as missing information and other quality concerns, data heterogeneity, and differing data formats. The nation's ability to make use of data depends heavily on the availability of a workforce that is properly trained and ready to tackle high-need areas. Training students to be capable in exploiting big data requires experience with statistical analysis, machine learning, and computational infrastructure that permits the real problems associated with massive data to be revealed and, ultimately, addressed. Analysis of big data requires cross-disciplinary skills, including the ability to make modeling decisions while balancing trade-offs between optimization and approximation, all while being attentive to useful metrics and system robustness. To develop those skills in students, it is important to identify whom to teach, that is, the educational background, experience, and characteristics of a prospective data-science student; what to teach, that is, the technical and practical content that should be taught to the student; and how to teach, that is, the structure and organization of a data-science program. Training Students to Extract Value from Big Data summarizes a workshop convened in April 2014 by the National Research Council's Committee on Applied and Theoretical Statistics to explore how best to train students to use big data. The workshop explored the need for training and curricula and coursework that should be included. One impetus for the workshop was the current fragmented view of what is meant by analysis of big data, data analytics, or data science. New graduate programs are introduced regularly, and they have their own notions of what is meant by those terms and, most important, of what students need to know to be proficient in data-intensive work. This report provides a variety of perspectives about those elements and about their integration into courses and curricula.
Training Data For Machine Learning
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Author : Anthony Sarkis
language : en
Publisher: O'Reilly Media
Release Date : 2022-07-19
Training Data For Machine Learning written by Anthony Sarkis 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 2022-07-19 with Computers categories.
Your training data has as much to do with the success of your data project as the algorithms themselves--most failures in deep learning systems relate to training data. But while training data is the foundation for successful machine learning, there are few comprehensive resources to help you ace the process. This hands-on guide explains how to work with and scale training data. Data science professionals and machine learning engineers will gain a solid understanding of the concepts, tools, and processes needed to: Design, deploy, and ship training data for production-grade deep learning applications Integrate with a growing ecosystem of tools Recognize and correct new training data-based failure modes Improve existing system performance and avoid development risks Confidently use automation and acceleration approaches to more effectively create training data Avoid data loss by structuring metadata around created datasets Clearly explain training data concepts to subject matter experts and other shareholders Successfully maintain, operate, and improve your system
Making The Most Of Data
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Author :
language : en
Publisher:
Release Date : 2015
Making The Most Of Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Tableau 10 Bootcamp
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Author : Joshua N. Milligan
language : en
Publisher: Packt Publishing
Release Date : 2017-09-26
Tableau 10 Bootcamp written by Joshua N. Milligan and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-26 with Computers categories.
Sharpen your data visualization skills with Tableau 10 Bootcamp.About This Book* Make informed decisions using powerful visualizations in Tableau* Learn effective data storytelling to transform how your business uses ideas* Use this extensive bootcamp that makes you an efficient Tableau user in a short span of timeWho This Book Is ForThis book caters to business, data, and analytics professionals who want to build rich interactive visualizations using Tableau Desktop. Familiarity with previous versions of Tableau will be helpful, but not necessary.What You Will Learn* Complete practical Tableau tasks with each chapter* Build different types of charts in Tableau with ease* Extend data using calculated fields and parameters* Prepare and refine data for analysis* Create engaging and interactive dashboards* Present data effectively using story pointsIn DetailTableau is a leading visual analytics software that can uncover insights for better and smarter decision-making. Tableau has an uncanny ability to beautify your data, compared to other BI tools, which makes it an ideal choice for performing fast and easy visual analysis.A military camp style fast-paced learning book that builds your understanding of Tableau 10 in no time. This day based learning guide contains the best elements from two of our published books, Learning Tableau 10 - Second Edition and Tableau 10 Business Intelligence Cookbook, and delivers practical, learning modules in manageable chunks. Each chunk is delivered in a "day", and each "day" is a productive day. Each day builds your competency in Tableau. You will increase your competence in integrating analytics and forecasting to enhance data analysis during the course of this Bootcamp.Each chapter presents core concepts and key takeaways about a topic in Tableau and provides a series of hands-on exercises. In addition to these exercises, at the end of the chapter, you will find self-check quizzes and extra drills to challenge you, to take what you learned to the next level. To summarize, this book will equip you with step-by-step instructions through rigorous tasks, practical callouts, and various real-world examples and assignments to reinforce your understanding of Tableau 10.Style and approachA fast paced book filled with highly-effective real-world examples to help you build new things and help you in solving problems in newer and unseen ways.
Data Centric Training Model
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Author : Gerard Blokdyk
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-10-15
Data Centric Training Model written by Gerard Blokdyk and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-15 with categories.
This limited edition data centric training model self-assessment will make you the established data centric training model domain specialist by revealing just what you need to know to be fluent and ready for any data centric training model challenge. How do I reduce the effort in the data centric training model work to be done to get problems solved? How can I ensure that plans of action include every data centric training model task and that every data centric training model outcome is in place? How will I save time investigating strategic and tactical options and ensuring data centric training model opportunity costs are low? How can I deliver tailored data centric training model advise instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all data centric training model essentials are covered, from every angle: the data centric training model self-assessment shows succinctly and clearly that what needs to be clarified to organize the business/project activities and processes so that data centric training model outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced data centric training model practitioners. Their mastery, combined with the uncommon elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in data centric training model are maximized with professional results. Your purchase includes access to the $249 value data centric training model self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.
Data Modeling Master Class Training Manual
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Author : Steve Hoberman
language : en
Publisher:
Release Date : 2015-07
Data Modeling Master Class Training Manual written by Steve Hoberman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07 with categories.
This is the sixth edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes. This text can be purchased prior to attending the Master Class, the latest course schedule and detailed description can be found on Steve Hoberman's website, stevehoberman.com. The Master Class is a complete data modeling course, containing three days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL data models. After learning the styles and steps in capturing and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard. You will know not just how to build a data model, but how to build a data model well. Two case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects. Top 10 Objectives 1.Explain data modeling components and identify them on your projects by following a question-driven approach 2.Demonstrate reading a data model of any size and complexity with the same confidence as reading a book 3.Validate any data model with key "settings" (scope, abstraction, timeframe, function, and format) as well as through the Data Model Scorecard 4.Apply requirements elicitation techniques including interviewing, artifact analysis, prototyping, and job shadowing 5.Build relational and dimensional conceptual and logical data models, and know the tradeoffs on the physical side for both RDBMS and NoSQL solutions 6.Practice finding structural soundness issues and standards violations 7.Recognize when to use abstraction and where patterns and industry data models can give us a great head start 8.Use a series of templates for capturing and validating requirements, and for data profiling 9.Evaluate definitions for clarity, completeness, and correctness 10.Leverage the Data Vault and enterprise data model for a successful
Data Training
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Author :
language : en
Publisher:
Release Date : 1988
Data Training written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Electronic data processing categories.