Oxford University Press

Machine Learning for Econometrics

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Year: 2025
Publisher: Oxford University Press
Language: English
Pages: 353
ISBN 10: 0198918836
ISBN 13: 9780198918837
File: PDF, 14.18 MB

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Additional information

Additional information

Authors

Christophe Gaillac & Jérémy L'Hour

Publisher

Oxford University Press

Published On

2025-06-13

Language

English

Identifiers

0198918836

ISBN

9780198918837

Format

14.18 MB, pdf

PAGES

353

Rating

⭐️⭐️⭐️⭐️⭐️ 4.35

Description

 

Machine Learning Econometrics Mastery

Machine Learning Econometrics Mastery empowers learners with cutting-edge machine learning techniques specifically tailored for econometric analysis. Consequently, this course bridges traditional econometrics with modern predictive analytics, enabling you to extract actionable insights from complex economic data.

Course Overview

In this comprehensive course, you will explore essential machine learning algorithms such as regression trees, random forests, support vector machines, LASSO and ridge regression, and neural networks. Importantly, each technique is explained in the context of real-world economic scenarios so you can apply them effectively in your research or industry projects.

What You’ll Learn

  • Understand foundational econometric principles while integrating machine learning approaches to enhance model accuracy and interpretability.
  • Apply supervised and unsupervised learning to economic data, including clustering consumer segments and forecasting GDP growth.
  • Evaluate model performance through cross-validation, ROC curves, and other key metrics that matter in economic prediction tasks.
  • Interpret and visualize results using advanced data visualization tools that highlight trends and anomalies in economic systems.
  • Build production-ready models that can be deployed for policy analysis, financial forecasting, and automated decision-making.

Who Should Enroll

This course suits economists, data scientists, statisticians, and analysts who want to upgrade their modeling toolkit with machine learning. Moreover, professionals aiming to stand out in fields like finance, public policy, and economic consulting will find immense value.

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Why This Course Matters

As economic systems grow more complex and data volumes expand rapidly, traditional models alone no longer suffice. Therefore, integrating machine learning with econometrics accelerates discovery and sharpens predictive precision. In addition, this course emphasizes hands‑on projects so that you can build portfolios showcasing your practical expertise. Above all, you will graduate ready to tackle economic forecasting challenges with confidence.

Enroll Today

Don’t miss this chance to transform your analytical capabilities. Join peers worldwide who are revolutionizing economic analysis with machine learning methods that deliver results. With structured lessons, real datasets, and supportive resources, you’ll progress quickly yet thoroughly.

 

Additional information

Authors

Christophe Gaillac & Jérémy L'Hour

Publisher

Oxford University Press

Published On

2025-06-13

Language

English

Identifiers

0198918836

ISBN

9780198918837

Format

14.18 MB, pdf

PAGES

353

Rating

⭐️⭐️⭐️⭐️⭐️ 4.35

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