Applied Machine Learning: Algorithms
Applied Machine Learning: Algorithms
Released: 4/15/2024
Duration: 1h 58m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 267 MB
Genre: eLearning | Language: English
Released: 4/15/2024
Duration: 1h 58m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 267 MB
Genre: eLearning | Language: English
With the growing importance of machine learning in almost every sector, professionals need a deeper understanding and practical approach to implementing ML algorithms effectively.
This course covers commonly used machine learning algorithms. Instructor Matt Harrison focuses on non-deep learning algorithms, covering PCA, clustering, linear and logistic regression, decision trees, random forests, and gradient boosting.
Join Matt in this course to understand common ML algorithms, learn their pros and cons, and develop hands-on skills to leverage them by following along with challenges and solutions in GitHub Codespaces.
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