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Author: Dr. Argenis Leon
Publisher: Packt Publishing Ltd
ISBN: 1801077754
Category : Computers
Languages : en
Pages : 301
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Book Description
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.
Author: Dr. Argenis Leon
Publisher: Packt Publishing Ltd
ISBN: 1801077754
Category : Computers
Languages : en
Pages : 301
Get Book Here
Book Description
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.
Author: Jens Teubner
Publisher: Morgan & Claypool Publishers
ISBN: 1627050612
Category : Computers
Languages : en
Pages : 120
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Book Description
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
Author: United States. National Aeronautics and Space Administration
Publisher:
ISBN:
Category :
Languages : en
Pages : 140
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Book Description
Author: Ivan Mistrik
Publisher: Morgan Kaufmann
ISBN: 0128093382
Category : Computers
Languages : en
Pages : 472
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Book Description
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
Author: Suresh Chandra Satapathy
Publisher: Springer
ISBN: 9811055475
Category : Technology & Engineering
Languages : en
Pages : 646
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Book Description
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.
Author: The European Society of Telemetry
Publisher: BoD – Books on Demand
ISBN: 3756845354
Category : Technology & Engineering
Languages : en
Pages : 242
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Book Description
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.
Author: NASA Scientific and Technical Information Facility
Publisher:
ISBN:
Category : Earth sciences
Languages : en
Pages : 620
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Book Description
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 1382
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Book Description
Author:
Publisher:
ISBN:
Category : Nuclear energy
Languages : en
Pages : 1108
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Book Description
NSA is a comprehensive collection of international nuclear science and technology literature for the period 1948 through 1976, pre-dating the prestigious INIS database, which began in 1970. NSA existed as a printed product (Volumes 1-33) initially, created by DOE's predecessor, the U.S. Atomic Energy Commission (AEC). NSA includes citations to scientific and technical reports from the AEC, the U.S. Energy Research and Development Administration and its contractors, plus other agencies and international organizations, universities, and industrial and research organizations. References to books, conference proceedings, papers, patents, dissertations, engineering drawings, and journal articles from worldwide sources are also included. Abstracts and full text are provided if available.
Author:
Publisher:
ISBN:
Category : Data centers
Languages : en
Pages : 720
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Book Description
Comprehensive directory of databases as well as services "involved in the production and distribution of information in electronic form." There is a detailed subject index and function/service classification as well as name, keyword, and geographical location indexes.
