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Machine Learning y Regresión con PySpark. Guía paso a paso
Coursera Project Network

Machine Learning y Regresión con PySpark. Guía paso a paso

Leire Ahedo

Instructor: Leire Ahedo

142 already enrolled

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Beginner level

Recommended experience

2 hours (approximately)
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning

What you'll learn

  • Aprender los fundamentos de Apache Spark y MLlib

  • Generar un modelo de regresión con MLlib y PySpark de principio a fin

  • Comprender en profundidad el funcionamiento de los modelos de regresión

Skills you'll practice

  • Category: Machine Learning
  • Category: Jupyter notebooks
  • Category: PySpark

Details to know

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Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Beginner level

Recommended experience

2 hours (approximately)
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning

Learn, practice, and apply job-ready skills in less than 2 hours

  • Receive training from industry experts
  • Gain hands-on experience solving real-world job tasks
  • Build confidence using the latest tools and technologies
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About this Guided Project

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Fundamentos de Spark  y Jupyter Notebooks

  2. Fundamentos de regresión con MLlib en PySpark

  3. Carga y Preprocesamiento de datos con PySpark

  4. Entrenamiento de modelos y optimización con MLlib

  5. Predicciones y evaluación de modelos

Recommended experience

Fundamentos de Python

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Instructor

Leire Ahedo
Coursera Project Network
69 Courses23,633 learners

Offered by

How you'll learn

  • Skill-based, hands-on learning

    Practice new skills by completing job-related tasks.

  • Expert guidance

    Follow along with pre-recorded videos from experts using a unique side-by-side interface.

  • No downloads or installation required

    Access the tools and resources you need in a pre-configured cloud workspace.

  • Available only on desktop

    This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.

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