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Data Processing with Optimus

Author: Dr. Argenis Leon

Publisher: Packt Publishing Ltd

Published: 2021-09-03

Total Pages: 301

ISBN-13: 1801077754

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Written by the core Optimus team, this comprehensive guide will help you to understand how Optimus improves the whole data processing landscape Key FeaturesLoad, merge, and save small and big data efficiently with OptimusLearn Optimus functions for data analytics, feature engineering, machine learning, cross-validation, and NLPDiscover how Optimus improves other data frame technologies and helps you speed up your data processing tasksBook Description Optimus is a Python library that works as a unified API for data cleaning, processing, and merging data. It can be used for handling small and big data on your local laptop or on remote clusters using CPUs or GPUs. The book begins by covering the internals of Optimus and how it works in tandem with the existing technologies to serve your data processing needs. You'll then learn how to use Optimus for loading and saving data from text data formats such as CSV and JSON files, exploring binary files such as Excel, and for columnar data processing with Parquet, Avro, and OCR. Next, you'll get to grips with the profiler and its data types - a unique feature of Optimus Dataframe that assists with data quality. You'll see how to use the plots available in Optimus such as histogram, frequency charts, and scatter and box plots, and understand how Optimus lets you connect to libraries such as Plotly and Altair. You'll also delve into advanced applications such as feature engineering, machine learning, cross-validation, and natural language processing functions and explore the advancements in Optimus. Finally, you'll learn how to create data cleaning and transformation functions and add a hypothetical new data processing engine with Optimus. By the end of this book, you'll be able to improve your data science workflow with Optimus easily. What you will learnUse over 100 data processing functions over columns and other string-like valuesReshape and pivot data to get the output in the required formatFind out how to plot histograms, frequency charts, scatter plots, box plots, and moreConnect Optimus with popular Python visualization libraries such as Plotly and AltairApply string clustering techniques to normalize stringsDiscover functions to explore, fix, and remove poor quality dataUse advanced techniques to remove outliers from your dataAdd engines and custom functions to clean, process, and merge dataWho this book is for This book is for Python developers who want to explore, transform, and prepare big data for machine learning, analytics, and reporting using Optimus, a unified API to work with Pandas, Dask, cuDF, Dask-cuDF, Vaex, and Spark. Although not necessary, beginner-level knowledge of Python will be helpful. Basic knowledge of the CLI is required to install Optimus and its requirements. For using GPU technologies, you'll need an NVIDIA graphics card compatible with NVIDIA's RAPIDS library, which is compatible with Windows 10 and Linux.

Book Synopsis Data Processing with Optimus by : Dr. Argenis Leon

Download or read book Data Processing with Optimus written by Dr. Argenis Leon and published by Packt Publishing Ltd. This book was released on 2021-09-03 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by the core Optimus team, this comprehensive guide will help you to understand how Optimus improves the whole data processing landscape Key FeaturesLoad, merge, and save small and big data efficiently with OptimusLearn Optimus functions for data analytics, feature engineering, machine learning, cross-validation, and NLPDiscover how Optimus improves other data frame technologies and helps you speed up your data processing tasksBook Description Optimus is a Python library that works as a unified API for data cleaning, processing, and merging data. It can be used for handling small and big data on your local laptop or on remote clusters using CPUs or GPUs. The book begins by covering the internals of Optimus and how it works in tandem with the existing technologies to serve your data processing needs. You'll then learn how to use Optimus for loading and saving data from text data formats such as CSV and JSON files, exploring binary files such as Excel, and for columnar data processing with Parquet, Avro, and OCR. Next, you'll get to grips with the profiler and its data types - a unique feature of Optimus Dataframe that assists with data quality. You'll see how to use the plots available in Optimus such as histogram, frequency charts, and scatter and box plots, and understand how Optimus lets you connect to libraries such as Plotly and Altair. You'll also delve into advanced applications such as feature engineering, machine learning, cross-validation, and natural language processing functions and explore the advancements in Optimus. Finally, you'll learn how to create data cleaning and transformation functions and add a hypothetical new data processing engine with Optimus. By the end of this book, you'll be able to improve your data science workflow with Optimus easily. What you will learnUse over 100 data processing functions over columns and other string-like valuesReshape and pivot data to get the output in the required formatFind out how to plot histograms, frequency charts, scatter plots, box plots, and moreConnect Optimus with popular Python visualization libraries such as Plotly and AltairApply string clustering techniques to normalize stringsDiscover functions to explore, fix, and remove poor quality dataUse advanced techniques to remove outliers from your dataAdd engines and custom functions to clean, process, and merge dataWho this book is for This book is for Python developers who want to explore, transform, and prepare big data for machine learning, analytics, and reporting using Optimus, a unified API to work with Pandas, Dask, cuDF, Dask-cuDF, Vaex, and Spark. Although not necessary, beginner-level knowledge of Python will be helpful. Basic knowledge of the CLI is required to install Optimus and its requirements. For using GPU technologies, you'll need an NVIDIA graphics card compatible with NVIDIA's RAPIDS library, which is compatible with Windows 10 and Linux.

Data Processing on FPGAs

Author: Jens Teubner

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 104

ISBN-13: 3031018494

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Roughly a decade ago, power consumption and heat dissipation concerns forced the semiconductor industry to radically change its course, shifting from sequential to parallel computing. Unfortunately, improving performance of applications has now become much more difficult than in the good old days of frequency scaling. This is also affecting databases and data processing applications in general, and has led to the popularity of so-called data appliances—specialized data processing engines, where software and hardware are sold together in a closed box. Field-programmable gate arrays (FPGAs) increasingly play an important role in such systems. FPGAs are attractive because the performance gains of specialized hardware can be significant, while power consumption is much less than that of commodity processors. On the other hand, FPGAs are way more flexible than hard-wired circuits (ASICs) and can be integrated into complex systems in many different ways, e.g., directly in the network for a high-frequency trading application. This book gives an introduction to FPGA technology targeted at a database audience. In the first few chapters, we explain in detail the inner workings of FPGAs. Then we discuss techniques and design patterns that help mapping algorithms to FPGA hardware so that the inherent parallelism of these devices can be leveraged in an optimal way. Finally, the book will illustrate a number of concrete examples that exploit different advantages of FPGAs for data processing. Table of Contents: Preface / Introduction / A Primer in Hardware Design / FPGAs / FPGA Programming Models / Data Stream Processing / Accelerated DB Operators / Secure Data Processing / Conclusions / Bibliography / Authors' Biographies / Index

Book Synopsis Data Processing on FPGAs by : Jens Teubner

Download or read book Data Processing on FPGAs written by Jens Teubner and published by Springer Nature. This book was released on 2022-05-31 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Roughly a decade ago, power consumption and heat dissipation concerns forced the semiconductor industry to radically change its course, shifting from sequential to parallel computing. Unfortunately, improving performance of applications has now become much more difficult than in the good old days of frequency scaling. This is also affecting databases and data processing applications in general, and has led to the popularity of so-called data appliances—specialized data processing engines, where software and hardware are sold together in a closed box. Field-programmable gate arrays (FPGAs) increasingly play an important role in such systems. FPGAs are attractive because the performance gains of specialized hardware can be significant, while power consumption is much less than that of commodity processors. On the other hand, FPGAs are way more flexible than hard-wired circuits (ASICs) and can be integrated into complex systems in many different ways, e.g., directly in the network for a high-frequency trading application. This book gives an introduction to FPGA technology targeted at a database audience. In the first few chapters, we explain in detail the inner workings of FPGAs. Then we discuss techniques and design patterns that help mapping algorithms to FPGA hardware so that the inherent parallelism of these devices can be leveraged in an optimal way. Finally, the book will illustrate a number of concrete examples that exploit different advantages of FPGAs for data processing. Table of Contents: Preface / Introduction / A Primer in Hardware Design / FPGAs / FPGA Programming Models / Data Stream Processing / Accelerated DB Operators / Secure Data Processing / Conclusions / Bibliography / Authors' Biographies / Index

Proceedings of the European Test and Telemetry Conference ettc2022

Author: The European Society of Telemetry

Publisher: BoD – Books on Demand

Published: 2022-10-27

Total Pages: 240

ISBN-13: 3756848361

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The way we prepare and analyse tests has evolved, as well as the way we perform and conduct those tests. However, we all concluded that the face-to-face exchange could not be replaced by any digital event. The ettc2022 was the first in-person telemetry event since the outbreak of the pandemic in 2020. The conference presented a dense technical program of more than 40 high quality papers, merged in the Conference Proceedings. As always, you could find the latest and most promising methods here but also hardware and software ideas for the telemetry solutions of tomorrow.

Book Synopsis Proceedings of the European Test and Telemetry Conference ettc2022 by : The European Society of Telemetry

Download or read book Proceedings of the European Test and Telemetry Conference ettc2022 written by The European Society of Telemetry and published by BoD – Books on Demand. This book was released on 2022-10-27 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: The way we prepare and analyse tests has evolved, as well as the way we perform and conduct those tests. However, we all concluded that the face-to-face exchange could not be replaced by any digital event. The ettc2022 was the first in-person telemetry event since the outbreak of the pandemic in 2020. The conference presented a dense technical program of more than 40 high quality papers, merged in the Conference Proceedings. As always, you could find the latest and most promising methods here but also hardware and software ideas for the telemetry solutions of tomorrow.

Software Architecture for Big Data and the Cloud

Author: Ivan Mistrik

Publisher: Morgan Kaufmann

Published: 2017-06-12

Total Pages: 470

ISBN-13: 0128093382

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Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques Presents case studies involving enterprise, business, and government service deployment of big data applications Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data

Book Synopsis Software Architecture for Big Data and the Cloud by : Ivan Mistrik

Download or read book Software Architecture for Big Data and the Cloud written by Ivan Mistrik and published by Morgan Kaufmann. This book was released on 2017-06-12 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques Presents case studies involving enterprise, business, and government service deployment of big data applications Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data

Data Management, Analytics and Innovation

Author: Neha Sharma

Publisher: Springer Nature

Published: 2020-08-18

Total Pages: 476

ISBN-13: 9811556164

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This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.

Book Synopsis Data Management, Analytics and Innovation by : Neha Sharma

Download or read book Data Management, Analytics and Innovation written by Neha Sharma and published by Springer Nature. This book was released on 2020-08-18 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.

Automatic Data Processing: System/360 Edition

Author: Frederick P. Brooks (Jr.)

Publisher: John Wiley & Sons

Published: 1969

Total Pages: 504

ISBN-13:

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USA. Computer science textbook on EDP and the fundamental techniques of data analysis, data processing and computer programming - includes chapters on manual data processing equipment, punched card equipment, computer coding, computer organization, programming, searching and sorting, programming systems, systems design, etc. Diagrams, flow charts and references.

Book Synopsis Automatic Data Processing: System/360 Edition by : Frederick P. Brooks (Jr.)

Download or read book Automatic Data Processing: System/360 Edition written by Frederick P. Brooks (Jr.) and published by John Wiley & Sons. This book was released on 1969 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: USA. Computer science textbook on EDP and the fundamental techniques of data analysis, data processing and computer programming - includes chapters on manual data processing equipment, punched card equipment, computer coding, computer organization, programming, searching and sorting, programming systems, systems design, etc. Diagrams, flow charts and references.

NASA SP-7500

Author: United States. National Aeronautics and Space Administration

Publisher:

Published: 1972

Total Pages: 140

ISBN-13:

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Book Synopsis NASA SP-7500 by : United States. National Aeronautics and Space Administration

Download or read book NASA SP-7500 written by United States. National Aeronautics and Space Administration and published by . This book was released on 1972 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Smart Computing and Informatics

Author: Suresh Chandra Satapathy

Publisher: Springer

Published: 2017-10-28

Total Pages: 653

ISBN-13: 9811055475

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This volume contains 68 papers presented at SCI 2016: First International Conference on Smart Computing and Informatics. The conference was held during 3-4 March 2017, Visakhapatnam, India and organized communally by ANITS, Visakhapatnam and supported technically by CSI Division V – Education and Research and PRF, Vizag. This volume contains papers mainly focused on smart computing for cloud storage, data mining and software analysis, and image processing.

Book Synopsis Smart Computing and Informatics by : Suresh Chandra Satapathy

Download or read book Smart Computing and Informatics written by Suresh Chandra Satapathy and published by Springer. This book was released on 2017-10-28 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains 68 papers presented at SCI 2016: First International Conference on Smart Computing and Informatics. The conference was held during 3-4 March 2017, Visakhapatnam, India and organized communally by ANITS, Visakhapatnam and supported technically by CSI Division V – Education and Research and PRF, Vizag. This volume contains papers mainly focused on smart computing for cloud storage, data mining and software analysis, and image processing.

Scientific and Technical Aerospace Reports

Author:

Publisher:

Published: 1965

Total Pages: 1372

ISBN-13:

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Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.

Book Synopsis Scientific and Technical Aerospace Reports by :

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1965 with total page 1372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.

Modern Data Processing

Author: Robert R. Arnold

Publisher: John Wiley & Sons

Published: 1978

Total Pages: 464

ISBN-13:

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Fundamentals of data processing; History of data processing; Data processing applications; Manual and mechanical data processing; Recording data for computer processing; Electronic data processing: introduction; EDP central processing unit; EDP auxiliary storage; EDP input-output devices.

Book Synopsis Modern Data Processing by : Robert R. Arnold

Download or read book Modern Data Processing written by Robert R. Arnold and published by John Wiley & Sons. This book was released on 1978 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of data processing; History of data processing; Data processing applications; Manual and mechanical data processing; Recording data for computer processing; Electronic data processing: introduction; EDP central processing unit; EDP auxiliary storage; EDP input-output devices.