Enhancing Data Science Outcomes With Efficient Workflow (EDSOEW)

 

Course Overview

Learn how to create an end-to-end, hardware-accelerated machine learning pipeline for large datasets. Throughout the development process, you’ll use diagnostic tools to identify delays and learn to mitigate common pitfalls.

Pré- requisitos

  • Basic knowledge of a standard data science workflow on tabular data. To gain an adequate understanding, we recommend this article.
  • Knowledge of distributed computing using Dask. To gain an adequate understanding, we recommend the “Get Started” guide from Dask.
  • Completion of the DLI’s Fundamentals of Accelerated Data Science course or an ability to manipulate data using cuDF and some experience building machine learning models using cuML.

Objetivos do Curso

  • Develop and deploy an accelerated end-to-end data processing pipeline for large datasets
  • Scale data science workflows using distributed computing
  • Perform DataFrame transformations that take advantage of hardware acceleration and avoid hidden slowdowns
  • Enhance machine learning solutions through feature engineering and rapid experimentation
  • Improve data processing pipeline performance by optimizing memory management and hardware utilization

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Preços & Delivery methods

Treinamento online

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0,5 dias

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Classroom training

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Instructor-led Online Training:   Este é um curso Instructor-Led Online. If you have any questions about our online courses, feel free to contact us via phone or Email anytime.

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Treinamento online 07:30 Pacific Daylight Time (PDT) Este curso está sendo entregue por um parceiro Inscrever