LinkedIn – Applied Machine Learning: Algorithms 2024-4

Applied Machine Learning: Algorithms course. With the increasing importance of machine learning in almost every field, professionals need a deeper understanding and practical approach to implement machine learning algorithms effectively. This course covers common machine learning algorithms. The course instructor, Matt Harrison, focuses on non-deep learning algorithms and covers PCA, clustering, linear and logistic regression, decision trees, random forests, and slope boosting. By taking this course with Matt, understand common machine learning algorithms, learn their pros and cons, and develop the practical skills to use them by following challenges and solutions on GitHub Codespaces.

What you will learn

• Understand common machine learning algorithms such as K-means, PCA, linear and logistic regression, decision trees, random forests, and slope boosting.
• Learn the pros and cons of each algorithm.
• Develop your practical skills to use machine learning algorithms to solve real-world problems.
• Learn how to use GitHub Codespaces to practice your skills.

This course is suitable for people who

• Interested in learning how to use machine learning algorithms to solve real-world problems.
• Have prior knowledge of machine learning and seek a deeper and more practical understanding of common algorithms.
• Want to improve their machine learning skills using GitHub Codespaces.