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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
12,183 個評分
2,916 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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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:

2401 - 机器学习基础:案例研究 的 2425 個評論(共 2,826 個)

創建者 Jay D S

2020年9月18日

this course should include some more coding about python in manchine learning and knn

創建者 Ibrahim G

2017年8月29日

it's very cool base and i hope next specialization course will get more into details.

創建者 Deleted A

2017年10月23日

The first week was a little chatty but the content of the rest of the weeks is good.

創建者 Chin-Teng H

2017年7月15日

bomb bad awful interest present immutable sad great time tack how hungry hungry opps

創建者 Hakim L

2018年12月3日

Good course despite the technical issues with GraphLab Create in Coursera Notebook.

創建者 张宸恺

2016年10月10日

Good on presenting and using ML tools, but the part of principle is not good enough

創建者 Mateusz B R P S z o o N D 3 0 W

2015年12月31日

I enjoyed this course but I think assignments could be a little bit more difficult.

創建者 Satyam R

2020年9月15日

Thanks a lot for providing such intuitive approach towards the ML and DL Concepts.

創建者 Kim K

2016年3月23日

a very good introduction for machine learning with good examples and explainations

創建者 Shyam A

2020年7月7日

good, But check whether your pc can run on graphlab before taking up this course.

創建者 Sachin R G

2020年6月13日

Need some improvement like much more focus on statistical concepts behind program

創建者 Shashikant K

2020年6月9日

This is very good course. This is helpful for me. Some problem on using graphlab.

創建者 Anurag G

2020年7月22日

Preety good course but instead of Sframe , i prefer pandas and sklearn libraries

創建者 Durga P S

2018年9月9日

Very nice foundation course in Machine Learning especially with GraphLab create.

創建者 Henrik

2016年7月2日

Very nice content but dont like we use graphlab since i wont use it after course

創建者 vivekanandhan

2016年3月28日

Last module on Deep learning is not explained well as compared to other modules.

創建者 Xun Y

2018年9月8日

great introductory course to machine learning, includes almost all the aspects.

創建者 Zynab S

2016年6月30日

very good for one who has no idea about machine learning , but I dont like dato

創建者 Bruno C K

2015年12月12日

very nice! A little bit more of reading material would be interesting, though..

創建者 MUBEEN M

2021年1月29日

hands on material is overly simplified perhaps because it is foundation course

創建者 Ankita S

2020年10月14日

Great course !! With practical knowledge and the trending topics are captured.

創建者 Mrutyunjaya S Y

2020年5月16日

It given more understanding of all concepts..Its really helpfull for beginners

創建者 mikhil i

2016年12月1日

The deep learning part of the course needs to be better done. The rest is good

創建者 Ricky W

2016年2月10日

Very nice introduction to Machine Learning and to Python programming language

創建者 Daniel B S d S

2016年11月2日

The course is great, but it would be greater if used open source free tools.