Hiring Data Scientists and Machine Learning Engineers

Hiring Data Scientists and Machine Learning Engineers
Author: Roy Keyes
Publisher:
Total Pages:
Release: 2021-08-30
Genre:
ISBN: 9781637905258

Hiring Data Scientists and Machine Learning Engineers is a concise, practical guide to help you hire the right people for your organization. The book will help you navigate the plethora of data science related roles and skills and help you create an effective hiring strategy to suit your organization's needs.

Visual Strategies

Visual Strategies
Author: Felice Frankel
Publisher: Yale University Press
Total Pages: 161
Release: 2012-01-01
Genre: Design
ISBN: 0300176449

Helps scientists and engineers to communicate research results by showing how to create effective graphics for use in journal submissions, grant proposals, conference posters, presentations and more.

Uncertainty Analysis for Engineers and Scientists

Uncertainty Analysis for Engineers and Scientists
Author: Faith A. Morrison
Publisher: Cambridge University Press
Total Pages: 389
Release: 2021-01-07
Genre: Computers
ISBN: 1108478352

Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various steps. Provides a systematic, worksheet-based process to determine error limits on measured quantities, and all likely sources of uncertainty are explored, measured or estimated. Features instructions on how to carry out error analysis using Excel and MATLABĀ®, making previously tedious calculations easy. Whether you are new to the sciences or an experienced engineer, this useful resource provides a practical approach to performing error analysis. Suitable as a text for a junior or senior level laboratory course in aerospace, chemical and mechanical engineering, and for professionals.

The MIT Guide to Science and Engineering Communication, second edition

The MIT Guide to Science and Engineering Communication, second edition
Author: James Paradis
Publisher: MIT Press
Total Pages: 335
Release: 2002-06-21
Genre: Language Arts & Disciplines
ISBN: 0262265524

A second edition of a popular guide to scientific and technical communication, updated to reflect recent changes in computer technology. This guide covers the basics of scientific and engineering communication, including defining an audience, working with collaborators, searching the literature, organizing and drafting documents, developing graphics, and documenting sources. The documents covered include memos, letters, proposals, progress reports, other types of reports, journal articles, oral presentations, instructions, and CVs and resumes. Throughout, the authors provide realistic examples from actual documents and situations. The materials, drawn from the authors' experience teaching scientific and technical communication, bridge the gap between the university novice and the seasoned professional. In the five years since the first edition was published, communication practices have been transformed by computer technology. Today, most correspondence is transmitted electronically, proposals are submitted online, reports are distributed to clients through intranets, journal articles are written for electronic transmission, and conference presentations are posted on the Web. Every chapter of the book reflects these changes. The second edition also includes a compact Handbook of Style and Usage that provides guidelines for sentence and paragraph structure, punctuation, and usage and presents many examples of strategies for improved style.

Statistical Inference for Engineers and Data Scientists

Statistical Inference for Engineers and Data Scientists
Author: Pierre Moulin
Publisher: Cambridge University Press
Total Pages: 423
Release: 2019
Genre: Mathematics
ISBN: 1107185920

A mathematically accessible textbook introducing all the tools needed to address modern inference problems in engineering and data science.

Enhancing the Postdoctoral Experience for Scientists and Engineers

Enhancing the Postdoctoral Experience for Scientists and Engineers
Author: Institute of Medicine
Publisher: National Academies Press
Total Pages: 210
Release: 2000-10-08
Genre: Education
ISBN: 0309069963

The concept of postdoctoral training came to science and engineering about a century ago. Since the 1960s, the performance of research in the United States has increasingly relied on these recent PhDs who work on a full-time, but on a temporary basis, to gain additional research experience in preparation for a professional research career. Such experiences are increasingly seen as central to careers in research, but for many, the postdoctoral experience falls short of expectations. Some postdocs indicate that they have not received the recognition, standing or compensation that is commensurate with their experience and skills. Is this the case? If so, how can the postdoctoral experience be enhanced for the over 40,000 individuals who hold these positions at university, government, and industry laboratories? This new book offers its assessment of the postdoctoral experience and provides principles, action points, and recommendations for enhancing that experience.

A Guide to Microsoft Excel 2007 for Scientists and Engineers

A Guide to Microsoft Excel 2007 for Scientists and Engineers
Author: Bernard V. Liengme
Publisher:
Total Pages: 326
Release: 2009
Genre: Engineering
ISBN:

Completely updated guide for scientists, engineers and students who want to use Microsoft Excel 2007 to its full potential. Electronic spreadsheet analysis has become part of the everyday work of researchers in all areas of engineering and science. Microsoft Excel, as the industry standard spreadsheet, has a range of scientific functions that can be utilized for the modeling, analysis and presentation of quantitative data. This text provides a straightforward guide to using these functions of Microsoft Excel, guiding the reader from basic principles through to more complicated areas such as formulae, charts, curve-fitting, equation solving, integration, macros, statistical functions, and presenting quantitative data.

Data Analysis

Data Analysis
Author: Siegmund Brandt
Publisher: Springer Science & Business Media
Total Pages: 532
Release: 2014-02-14
Genre: Science
ISBN: 3319037625

The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, in working for bachelor or master degrees, in thesis work, and in research and professional work.

Liengme's Guide to Excel 2016 for Scientists and Engineers

Liengme's Guide to Excel 2016 for Scientists and Engineers
Author: Bernard Liengme
Publisher: Academic Press
Total Pages: 416
Release: 2019-08-14
Genre: Computers
ISBN: 0128182504

Liengme's Guide to Excel 2016 for Scientists and Engineers is a completely updated guide for students, scientists, and engineers who want to use Microsoft Excel 2016 to its full potential, whether you're using a PC or a Mac. Electronic spreadsheet analysis has become part of the everyday work of researchers in all areas of engineering and science. Microsoft Excel, as the industry standard spreadsheet, has a range of scientific functions that can be utilized for the modeling, analysis, and presentation of quantitative data. This text provides a straightforward guide to using these functions of Microsoft Excel, guiding the reader from basic principles through to more complicated areas such as formulae, charts, curve-fitting, equation solving, integration, macros, statistical functions, and presenting quantitative data. - Content written specifically for the requirements of science and engineering students and professionals working with Microsoft Excel, brought fully up to date with Microsoft Office release of Excel 2016. - Features of Excel 2016 are illustrated through a wide variety of examples based on technical contexts, demonstrating the use of the program for analysis and presentation of experimental results. - Where appropriate, demonstrates the differences between the PC and Mac versions of Excel. - Includes many new end-of-chapter problems at varying levels of difficulty.

Cloud Computing for Science and Engineering

Cloud Computing for Science and Engineering
Author: Ian Foster
Publisher: MIT Press
Total Pages: 391
Release: 2017-09-29
Genre: Computers
ISBN: 0262037246

A guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. The book is accompanied by a website, Cloud4SciEng.org, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors.