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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
12,275 個評分
2,941 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....

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BL
2016年10月16日

Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much

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.

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2801 - 机器学习基础:案例研究 的 2825 個評論(共 2,853 個)

創建者 Joseph J F

2017年8月20日

It is more a course in using the tools designed by the teachers than machine learning. It might do something for a less experienced user in programming, but I didn't find it much use. The overview of Machine Learning tasks isn't bad.

創建者 Andras H

2020年5月31日

on one hand good... on other hand annoying ( mixing graphlab and turicreate... shitty wording of the assignment task, info added as side note which was vital for the assignments...etc.) The curse material would need a refresh.

創建者 Sunil T

2020年5月24日

SFrame data do not support by an updated version of the Python, so student won't able to finish their assignments. So instructor need to update the materials and database which is supported by a new version of Python

創建者 Tudor S

2018年4月22日

The Assignments and Quiz questions are hard to read and comprehend.

Although individually the course presentations are ok, overall this course isn't a very relevant or coherent introduction to Machine Learning.

創建者 Taylor I

2020年5月11日

Feel like I have been duped in a way. No capstone project and you are pretty much forced to use Turi Create (proprietary/black-box version of pandas), which I found incredibly hard to install and use.

創建者 Ashley

2019年6月23日

Content is outdated and should be revamp, the library use in this course is only for python 2.6 which is legacy and should be updated to latest python version using skicit learn instead of graphlab.

創建者 Arman A

2016年2月16日

The course uses proprietary tools for machine learning and data manipulation, making it effectively useless! However, the material on describing the machine learning algorithms were excellent!

創建者 Annemarie S

2019年5月24日

The instruction conceptually is fine, but I really disliked dealing with setting up Graph Lab Create and SFrames when we could have instead been using more commonly used open source software.

創建者 charan S

2017年7月16日

If someone is looking for ML foundations and what is ML, they can choose this course. This is very basic course and i feel should be excluded from the ML specialization.

創建者 Eiaki M

2016年3月5日

One would learn a thing or two, but the course is very sparse compared to other machine learning courses, and I didn't feel that it was worth the time and the cost.

創建者 Robert P M

2015年10月27日

I do not like this course being tied to a commercial product. In my opinion it should be using an open source python library and not focusing on the Dato product.

創建者 Evlampi H

2015年11月5日

The framework is ok, but it would be more insight on the functions would be much more amplifying the learning process.

Good working examples, though!

創建者 Piotr T

2015年10月6日

it's rather a course on using API of proprietary software with very very basic background on the actual math underneath

創建者 David F

2015年12月2日

I didn't like the python environment, I thought it will be more like Ng's course. Nice explanations, but for amateurs.

創建者 Patryk H

2015年10月14日

Due to many technical issues with GraphLab lib I have to reduce acitivity in this curse for only video viewing :(.

創建者 Elgardo E

2020年5月29日

Course videos are outdated and requires time to investigate and research. This causes wasted time and effort.

創建者 David H

2015年10月31日

Very, very high altitude introduction presented in a seemingly confused way with a lot of product placement.

創建者 Zuozhi W

2017年2月7日

TBH this class's experience is not good. The lecturers seem unprepared and they talk very repetitively.

創建者 Suhasini L

2020年9月4日

Not given details like what is a vector? people from non technical backgrounds will have tough time

創建者 ashish s g

2017年2月15日

Very good course material. However, Graphlab is no longer free to use for commercial purpose.

創建者 Mark F

2015年12月19日

This course is to much about graphlab and not enough about the mechanics of machine learning.

創建者 Najmeh R

2016年10月4日

The subjectes are not learnt deeply and precisely. Too summarized and vague!

創建者 tiafvoonug k x

2016年1月6日

As a non programer, or mathematician, this course is too hard to follow.

創建者 Ishank C

2020年6月6日

They Don't tech the mathematics behind the machine learning.

創建者 Satyam N

2018年3月26日

This course doesn't give any insight about the algorithms.