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Linkedin Learning Courses

Logo of telegram channel linkedin_learning — Linkedin Learning Courses L
Logo of telegram channel linkedin_learning — Linkedin Learning Courses
Channel address: @linkedin_learning
Categories: Education
Language: English
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2021-09-15 14:00:38 Exercice Files
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2021-09-15 14:00:37 Full description

The ability to apply machine learning algorithms is an important part of a data scientist’s skill set. scikit-learn is a popular open-source Python library that offers user-friendly and efficient versions of common machine learning algorithms. In this course, data scientist Michael Galarnyk explains how to use scikit-learn for supervised and unsupervised machine learning. Michael reviews the benefits of this easy-to-use API and then quickly segues to practical techniques, starting with linear and logistic regression, decision trees, and random forest models. In chapter three, he covers unsupervised learning techniques such as K-means clustering and principal component analysis (PCA). Plus, learn how to create scikit-learn pipelines to make your code cleaner and more resilient to bugs. By the end of the course, you'll be able to understand the strengths and weaknesses of each scikit-learn algorithm and build better, more efficient machine learning models.

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Udemy Courses - ZTM Courses - Course
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2021-09-15 14:00:37
Machine Learning with Scikit-Learn

2020-10-15 • 43m • Advanced
Michael Galarnyk

Learn to use scikit-learn, the popular open-source Python library, to build efficient machine learning models.

Topics: Scikit-Learn, Machine Learning, Python
LinkedIn Learning
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