Name: Applied Machine Learning: Techniques and Applications
Brand: Johns Hopkins University
Availability: OnlineOnly
Rating: 3.7 (6 reviews)

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学生对 Johns Hopkins University 提供的 Applied Machine Learning: Techniques and Applications 的评价和反馈

3.7

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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....

1 - Applied Machine Learning: Techniques and Applications 的 7 个评论（共 7 个）

创建者 Lok T N

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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

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Jan 26, 2025

Brilliant course for learning advanced machine learning !

创建者 Luis R

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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 Sergio G N O

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Oct 28, 2025

The instructor just read in the course and he forced me to program his way, that is very poor criteria. exam was way too challenging and not very clear

创建者 Luiz A S

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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.