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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
12,660 個評分
3,030 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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476 - 机器学习基础:案例研究 的 500 個評論(共 2,949 個)

創建者 Muhammad A

2018年11月5日

This course is very much helpful for me to get understanding about python, deep learning, neural networks and the things like this. Thank you so much for help and guide me a lot.

創建者 Pooja G

2018年8月7日

Loved the course content. Particularly loved the usage of iPython notebook. very relevant & useful. Special thanks to the course instructors for helping guide through the course.

創建者 Remy d R

2016年5月6日

Excellent course, highly recommended. Hands-on and really easy to follow. Would love some more background / reading about the applied statistics though (since this is new to me).

創建者 Cristhian C C

2020年6月23日

Very good course on the fundamentals of Machine Learning. It introduces introductory and practical regression analysis, classification, recommendation systems and deep learning.

創建者 Francisco P

2017年6月25日

Thanks to the teachers, they prepared exciting, complete and interesting clases. The course is very useful to understand the main areas in machine learning. Totally recommended!

創建者 jonathan g

2020年9月1日

The use of case studies helps a lot to understand the concepts easily. The teachers' presentations were very funny and clear to understand the concepts presented in the course.

創建者 Nikhil R

2019年7月11日

Really a great course for getting started in machine learning, it helped me a lot for learning the fundamentals before jumping to the more complex parts in the Machine learning

創建者 Daniel T

2016年10月9日

A fantastic course! The case study approach really makes a difference. I can't stand purely theoretical courses so this one really stands out. Best ML course online hands down.

創建者 Steven G L

2015年10月28日

This is a great course that presented a review of the introductory concepts of Machine Learning, furthermore the implementation of the techniques are simple and easy to deploy

創建者 Matt M

2015年10月19日

I have worked through a number of machine learning courses, and this is by far the best. The course materials and the ipython notebook walk-throughs are incredibly informative.

創建者 Sivakumar R

2018年9月18日

Very practical and use case based method allows to understand concepts. Hands on training brings confidence to non-software student like me. Thank you for the valuable course.

創建者 Nand B P

2017年6月27日

Best Introductory course for Machine Learning for beginners as it shows an abstract yet hands-on type of approach to cover all the important topics related to the ML concepts.

創建者 vivek m

2017年3月3日

Best course to get start with ML as it has lot of real world example to get your hand dirty, which will help us to develop approach 'how to solve real world problem using ML '

創建者 Farouq O

2016年2月3日

The course did a good job of balancing depth with breadth. It's a well rounded course that provides a a student with enough information to tackle intermediate-advanced topics.

創建者 Alexander B

2015年12月12日

Very best initial level course that will introduce anyone to one of the modern ml tools and its usage, with a bit of needed theoretical science (its only an approach aint it?)

創建者 Sagar S

2020年6月7日

This is a very well designed course to build the Machine Learning Foundations for any level. And also its a perfect segway to remaining detailed courses of the Specialization

創建者 Shah H

2019年12月6日

Enhance my knowledge in ML and skilled me to do best Research in my MS Study, Thanks to COURSERA and University of Washington to give financial aid to learn Machine Learning.

創建者 Parth P

2018年4月1日

Hey This is Excellent course for beginners. The homework assignments are designed to grasp concepts easily and in most practical way possible. Thanks for such a great course.

創建者 VITTE

2018年3月11日

Very interesting, useful, and up to date, this course gives the main ideas with clarity, and relevant applications, in a time format that is feasible for an active engineer.

創建者 Dheeraj A

2016年10月28日

Course combines Real Word Applications with simple implementation via IPython Notebooks. Professors

know their stuff but are super chill. Pretty good assignments and quizzes.

創建者 Scott W

2016年6月10日

Great way to warm up the class. Seeing how the various techniques and best practices should/can be used was very helpful in warming up for the more densely focused classes.

創建者 Omri R

2016年2月29日

This is a great intro to a range of topics in machine learning. I do recommend pursuing the entire specialization since this course only scratches the surface of each topic.

創建者 Marcus C

2016年2月8日

great course. This covers all types of machine learning techniques deep enough to get a basic idea how things work. Enjoyed a lot. Instructors are really fun to learn from.

創建者 Cissy S

2015年12月2日

Loving it so far! Can't wait for the other courses. The case study approach is spot on! This is the first coursera course that is worth something! Kudos to the instructors.

創建者 Pankaj K

2017年9月25日

Nice overview to ease into all the content!, Only bad this is they use sframe :( either make it opensource and in the mainstream use or provide the assignments in sklearn!