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Learner Reviews & Feedback for Applied Machine Learning: Techniques and Applications by Johns Hopkins University
About the Course
The course "Applied Machine Learning: Techniques and Applications" focuses on the practical use of machine learning across various domains, particularly in computer vision, data feature analysis, and model evaluation. Learners will gain hands-on experience with key techniques, such as image processing and supervised learning methods while mastering essential skills in data pre-processing and model evaluation.
This course stands out for its balance between foundational concepts and real-world applications, giving learners the opportunity to work with widely-used datasets and tools like scikit-learn. Topics include image classification, object detection, feature extraction, and the selection of evaluation metrics for assessing model performance.
By completing this course, learners will be equipped with the practical skills necessary to implement machine learning solutions, enabling them to apply these techniques to solve complex problems in data processing, computer vision, and more.
Top reviews
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1 - 6 of 6 Reviews for Applied Machine Learning: Techniques and Applications
By Lok T N
•Dec 31, 2024
The instructor is great. Some information is not taught directly but appears in the notebooks and quizzes.
By fidel m
•Jan 26, 2025
Brilliant course for learning advanced machine learning !
By Luis R
•Feb 9, 2025
The course is very insightful but i think it stays too much on the surface only, but have great material to go deeper.
By Luiz A S
•Sep 12, 2025
not really up to date (weka!!!, java 1.8), the quizzes not always follow the content. I was looking for a course that could raise my skills in the domain (I already have a good knowledge), the course does not fit this objective.
By Colin H
•Feb 27, 2025
Terrible. No resources provided. A waste of time
By Ommkumar P
•May 30, 2025
Worst thing