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Data Processing with Optimus. Supercharge big data preparation tasks for analytics and machine learning with Optimus using Dask and PySpark

(ebook) (audiobook) (audiobook) Książka w języku 1
Data Processing with Optimus. Supercharge big data preparation tasks for analytics and machine learning with Optimus using Dask and PySpark Dr. Argenis Leon, Luis Aguirre - okladka książki

Data Processing with Optimus. Supercharge big data preparation tasks for analytics and machine learning with Optimus using Dask and PySpark Dr. Argenis Leon, Luis Aguirre - okladka książki

Data Processing with Optimus. Supercharge big data preparation tasks for analytics and machine learning with Optimus using Dask and PySpark Dr. Argenis Leon, Luis Aguirre - audiobook MP3

Data Processing with Optimus. Supercharge big data preparation tasks for analytics and machine learning with Optimus using Dask and PySpark Dr. Argenis Leon, Luis Aguirre - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
300
Dostępne formaty:
     PDF
     ePub
     Mobi
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.

Wybrane bestsellery

O autorach książki

Argenis Leon created Optimus, an open-source python library built over PySpark aimed to provide an easy-to-use API to clean, process, and merge data at scale. Since 2012, Argenis has been working on big data-related projects using Postgres, MongoDB, Elasticsearch for social media data collection and analytics. In 2015, he started working on Machine learning projects in Retail, AdTech, and Real Estate in Venezuela and Mexico. In 2019 he created Bumblebee, a low-code open-source web platform to clean and wrangle big data using CPU and GPUs using NVIDIA RAPIDS. Nowadays Argenis is Co-founder and CTO of boitas (backed by YCombinator) a wholesale marketplace for SMB in Latin America.
Luis Aguirre began working with web development projects for Mood Agency in 2018, creating sites for brands from all across Latin America. One year later he started working on Bumblebee, a low-code web platform to transform data that uses Optimus. In mid-2020 he started participating in the Optimus project as a core developer; focusing on creating the easiest-to-use experience for both projects. In 2021 he started working on the Optimus REST API, a tool to allow requests from the web focused on data wrangling.

Packt Publishing - inne książki

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