Chevron Left
Machine Learning Foundations: A Case Study Approach に戻る

ワシントン大学(University of Washington) による Machine Learning Foundations: A Case Study Approach の受講者のレビューおよびフィードバック

4.6
13,185件の評価

コースについて

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python....

人気のレビュー

PM

2019年8月18日

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

SZ

2016年12月19日

Great course!

Emily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

フィルター:

Machine Learning Foundations: A Case Study Approach: 226 - 250 / 3,054 レビュー

by Daniyar M

2016年2月17日

by Teo J

2020年5月8日

by Sabarish V

2018年4月18日

by Hans G Q

2020年10月11日

by v s

2018年3月24日

by P0

2017年12月21日

by Bruno L

2016年12月19日

by Pravin J

2021年6月14日

by Aldo V M

2019年2月25日

by Iurii S

2017年10月15日

by Nelson P

2017年10月30日

by Rajat D

2017年10月20日

by Sivashankar G

2016年7月17日

by Bharat R

2017年7月30日

by Mesum R H

2017年10月16日

by Wilfrid L

2019年1月8日

by sunil k

2017年6月23日

by Tinsae G A

2016年9月24日

by Luigi P

2020年5月15日

by Dionysios Z

2016年10月2日

by Mohamadreza R

2021年9月9日

by Mubbasher K

2018年1月28日

by Alex V

2017年5月12日

by Steven R

2016年6月6日

by Renato P

2016年5月29日