Home AI Courses ML Algorithms: Supervised Learning Tip to Tail

ML Algorithms: Supervised Learning Tip to Tail

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This course concentrates on the fundamentals of machine learning, including decision trees, k-nearest neighbors, and support vector machines. It addresses data preparation and production challenges and requires a rudimentary understanding of Python, linear algebra, and statistics.

Key AI Functions:Machine Learning, Supervised Learning, Decision Tree

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Description for ML Algorithms: Supervised Learning Tip to Tail

The course delves into the fundamentals of a machine learning project, with a particular emphasis on support vector machines, decision trees, and k-nearest neighbors for the purpose of conducting real-world case studies.

It instructs on the comparison of data preparation procedures and the resolution of production challenges in the context of applied machine learning.

A fundamental comprehension of linear algebra and statistics, as well as a basic understanding of Python programming, are necessary.

This is the second course in the Applied Machine Learning Specialization, which is offered by the Alberta Machine Intelligence Institute and Coursera.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by Alberta Machine Intelligence Institute

Duration: 9 hours (approximately)

Schedule: Flexible

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