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返回到 Machine Learning Foundations: A Case Study Approach

学生对 University of Washington 提供的 Machine Learning Foundations: A Case Study Approach 的评价和反馈

4.6
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13,532 个评分

课程概述

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....

热门审阅

RM

Feb 2, 2022

I was very disappointed with the exclusion of the final courses and the capstone project. The most interesting part of specialization no longer exists and no plausible justification has been given.

AH

Mar 27, 2022

very nice course.If you have basic knowledge of python datastructure then this course is best to start data science.All contents are beginner friendly which makes this course easily understandable.

筛选依据：

2726 - Machine Learning Foundations: A Case Study Approach 的 2750 个评论（共 3,157 个）

创建者 James S

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Oct 7, 2016

dont really like the dependency with dato sframe or prop tools

创建者 paolo s

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Oct 5, 2016

It would be perfect if also cover a section on spark an mllib.

创建者 Marco J

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Jan 13, 2022

Klasse Kurs, nur bei Graphlab vs. Turicreate etwas verwirrend

创建者 yangxiaoqi

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Jan 28, 2018

可以在刚入门机器学习时候听一听这门课，能够知道机器学习在实际中如何应用的。但是要深入机器学习还是应当学学里面的数学知识的。

创建者 Johan M

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Jun 9, 2016

Excellent course. Looking forward to the rest of the courses.

创建者 David B

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Dec 3, 2015

A nice introduction to the various machine learning concepts.

创建者 P V P

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Jun 28, 2020

its very basic just used a python module in the whole period

创建者 SOWMYA P

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Jun 3, 2020

i understood many more in this course i understood properly.

创建者 kumar p

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Oct 15, 2015

Nice for learners who want to jump start in machine learning

创建者 Swapnil A

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Sep 6, 2020

Would have been a 5 start course if the content was updated

创建者 R C

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Oct 8, 2020

A bit superficial, better to merge with following courses

创建者 C M R

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Aug 4, 2020

VERY GOOD TEACHING AND GREAT INFORMATION IN THE LECTURES.

创建者 krishna p

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Jun 23, 2016

This is very good material for machine learning starters.

创建者 VJ

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Nov 15, 2015

good material. good presentation skills of the instructor

创建者 Le D N

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Jul 11, 2021

Everything is good except the library used in Course ;(

创建者 João G B A V

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Dec 4, 2017

Muito bom, os exemplos onlines poderiam ser interativos.

创建者 Milan C

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Oct 20, 2017

Nice overview about different Machine Learning concepts.

创建者 Jjclof

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Oct 17, 2016

Well-made.

Good teachers.

But a bit too simple. 4/5

Thanks.

创建者 Markus M

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Feb 10, 2016

Good structure, but maybe a bit too basic and slow pace.

创建者 Dai W

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Jan 3, 2016

I cannot review my completed homework. It's very boring.

创建者 Lena M

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Dec 22, 2015

Loved the course, the teachers, the case study approach.

创建者 DARSHI A

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Jul 11, 2020

It is a good course and proffesors are explaining cool.

创建者 Andy L

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Aug 4, 2017

Good introduction. Don't expect more than that though.

创建者 Wangjun

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Dec 28, 2016

This course is very good.Thankyou for all the teachers.

创建者 SUHARIKA V

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Nov 26, 2021

the experiance is good and assignments are interesting