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Inicio 4 June 2026 04:41

Fin 4 June 2026

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Machine Learning: Regression

Explora el fascinante mundo del aprendizaje automático con un enfoque en la regresión en este curso integral titulado "Aprendizaje Automático: Regresión", ofrecido por la Universidad de Washington a través de Coursera. Sumérgete en un estudio de caso práctico sobre la predicción de precios de viviendas, donde emplearás modelos para pronosticar un v.
University of Washington via Coursera

University of Washington

9 Cursos


La Universidad de Washington es una universidad pública de alto rango en Seattle que ofrece una educación de clase mundial a estudiantes de todos los orígenes. Su diverso profesorado, amplias oportunidades de investigación y currículo innovador crean una experiencia de aprendizaje inigualable.

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Resumen

Explore the fascinating world of machine learning with a focus on regression in this comprehensive course titled "Machine Learning:

Regression", offered by the University of Washington through Coursera. Delve into a practical case study on predicting housing prices, where you'll employ models to forecast a continuous value - the price - based on input features such as square footage and the number of bedrooms and bathrooms.

This course illustrates the versatility of regression, applying it to various fields including medicine, finance, high-performance computing, and genetics.

Throughout this engaging program, you will gain hands-on experience with regularized linear regression models, mastering prediction and feature selection. Learn to manage extensive sets of features, choose between models of different complexities, and understand the effects of data peculiarities, like outliers, on your models and predictions.

This course equips you with the skills to implement optimization algorithms optimized for large datasets.

Key learning outcomes include:

  • Understanding the inputs and outputs of a regression model.
  • Distinguishing between bias and variance in data modeling.
  • Estimating model parameters through optimization algorithms.
  • Utilizing cross-validation for parameter tuning.
  • Evaluating model performance effectively.
  • Exploring the concept of sparsity and the role of LASSO in achieving sparse solutions.
  • Choosing appropriate models through deployment methods.
  • Making accurate predictions using your model.
  • Creating a regression model for price prediction using a housing dataset.
  • Applying these techniques using Python.

This course belongs to several important categories, including Artificial Intelligence Courses, Python Courses, and Machine Learning Courses, making it a perfect fit for individuals eager to explore the intersection of technology and practical application. Start your journey into the world of machine learning and regression with this expertly designed course.


Impartido por

Carlos Guestrin and Emily Fox


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