Learn how to build and evaluate machine learning models using scikit-learn, from data preprocessing to model selection and evaluation.
Intermediate
55 Lessons
27h
Certificate of Completion
Learn how to build and evaluate machine learning models using scikit-learn, from data preprocessing to model selection and evaluation.
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This course includes
This course includes
Course Overview
This comprehensive course is designed to develop the knowledge and skills to effectively utilize the scikit-learn library in Python for machine learning tasks. It is an excellent resource to help you develop practical machine learning applications using Python and scikit-learn. In this course, you’ll learn fundamental concepts such as supervised and unsupervised learning, data preprocessing, and model evaluation. You’ll also learn how to implement popular machine learning algorithms, including regression, ...Show More
What You'll Learn
An understanding of data preprocessing steps
Proficiency in model selection and evaluation
Implementation level skills for designing supervised learning algorithms
An insight into unsupervised learning techniques
Working knowledge of hyperparameter tuning and optimization
What You'll Learn
An understanding of data preprocessing steps
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Course Content
Course Overview
Introduction to Machine Learning
Preprocessing
Supervised Learning
Unsupervised Learning
Model Evaluation
9 Lessons
Tips and Tricks
8 Lessons
Conclusion
1 Lesson
Course Author
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Emma Bostian 🐞
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Evan Dunbar
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Carlos Matias La Borde
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Vinay Krishnaiah
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Anthony Walker
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Emma Bostian 🐞
@EmmaBostian
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