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返回到 机器学习基础：案例研究

學生對 华盛顿大学 提供的 机器学习基础：案例研究 的評價和反饋

4.6
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12,176 個評分
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2,913 條評論

課程概述

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....

熱門審閱

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.\n\nThe forums and discussions were really useful and helpful while doing the assignments.

SZ
2016年12月19日

Great course!\n\nEmily 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.

篩選依據：

2426 - 机器学习基础：案例研究 的 2450 個評論（共 2,824 個）

創建者 Marco P

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2015年12月4日

The homework assignments were not really about having understood the course

創建者 Sourabh K

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2020年6月30日

numpy and pandas are more preferable, but the overall experience was good.

創建者 George B

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2018年5月17日

Pretty great course. Really enjoyed it and looking forward to new courses

創建者 Jeffrey v S

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2017年10月31日

Content is good but the delivery is somewhat awkward and chatty at times.

創建者 Brennan W

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2017年2月4日

Was a good intro to different kinds of ML. Wish we had used SciKit-Learn.

創建者 Nandan S

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2018年3月15日

very good overall. The last week (Neural networks) is a little too fast.

創建者 Ramesh S

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2018年3月14日

A good and quick introduction to ML. Like the Case Study based approach.

創建者 Anastasiia

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2018年2月2日

OK course if you don't have any background knowledge. Graphlab oriented.

創建者 Aaron M

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2017年7月2日

Seems a bit old but it was a great way to introduce myself to the basics

創建者 Matías G

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2016年10月7日

Great Course, just felt little weak the last module about deep learning.

創建者 Xiaosong L

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2015年12月18日

a good introduction of the topics. I like the ML diagram in each module.

創建者 Lucia d E P

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2018年2月5日

I enjoyed the course and the fact that it uses Python for the exercises

創建者 Xavier H

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2016年8月8日

A good introduction tot he tools and possibilities of machine learning.

創建者 Zhe W

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2015年10月27日

Useful course to get general idea to get onboard with Machine Learning.

創建者 Leon

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2019年10月1日

Goes through many topics, but not as in depth as one would have liked.

創建者 Jacques J

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2017年9月8日

Was so good to get some exposure to the different areas of application

創建者 Sandeep K S

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2016年1月5日

Good course with the overview of different machine learning techniques

創建者 fredfoucart

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2015年12月10日

A good global introduction and simply explained. With fun as well....

創建者 Ali N

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2015年11月13日

Really great course content, but the assignments could become better.

創建者 Harshal M

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2017年8月18日

Great Course!! Helped me learning new things. Great way of teaching.

創建者 federico w

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2016年4月4日

Great course. Super case driven approach, professors are very clear.

創建者 أحمد ج

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2019年8月6日

wish to use more common ML libraries, but the content was very good

創建者 Kushvanth R

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2021年1月21日

All is well, but instructors could have used more common libraries

創建者 Bruno G E

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2016年4月17日

Just the tip of the iceberg, you'll want to dive in on each topic.

創建者 Tina W

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2019年4月2日

Good Intro course and familiarize yourself with iPython notebook.

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