返回到 Applied Machine Learning: Techniques and Applications
学生对 Johns Hopkins University 提供的 Applied Machine Learning: Techniques and Applications 的评价和反馈
10 个评分
课程概述
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.
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1 - Applied Machine Learning: Techniques and Applications 的 6 个评论（共 6 个）
创建者 Lok T N
•Dec 31, 2024
The instructor is great. Some information is not taught directly but appears in the notebooks and quizzes.
创建者 fidel m
•Jan 26, 2025
Brilliant course for learning advanced machine learning !
创建者 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.
创建者 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.
创建者 Colin H
•Feb 27, 2025
Terrible. No resources provided. A waste of time
创建者 Ommkumar P
•May 30, 2025
Worst thing