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Machine Learning Foundations: A Case Study Approach(으)로 돌아가기

워싱턴 대학교의 Machine Learning Foundations: A Case Study Approach 학습자 리뷰 및 피드백

4.6
별점
12,752개의 평가
3,045개의 리뷰

강좌 소개

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....

최상위 리뷰

PM
2019년 8월 18일

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
2016년 12월 19일

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.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,967개 리뷰 중 2826~2850

교육 기관: Uday K

2017년 5월 1일

The theories for the models should be explained in more detail and with few more examples.

교육 기관: Alexander B

2015년 11월 4일

lectures were well done, but the strong focus on using graphlab ruined this course for me

교육 기관: Naveen M N S

2016년 2월 7일

Decent course. Not very satisfied with the assignments as they are suited for graphlab

교육 기관: Carlos A C L

2021년 1월 25일

all lectures are obsoleta, and it's neccesary to install a WSL, the rest very well.

교육 기관: Saket D

2018년 2월 28일

Would have been great if anything compatible with python 3 was used in the course.

교육 기관: kaushik g

2018년 3월 25일

Content was good but was few years old and things are pacing up a bit these days.

교육 기관: amin s

2019년 5월 29일

primitive course, didn't expect this low standard from university of Washington

교육 기관: Rajiv K

2020년 6월 20일

Have to improve for other environment.

have to explain other alternative too.

교육 기관: Vamshi S G

2020년 6월 27일

i think the course should be updated, graphlab and some other are outdated.

교육 기관: Julien F

2017년 11월 16일

Some quiz questions were vague and/or ambiguous, or not covered in talks.

교육 기관: Marco M

2015년 12월 4일

Too much synthetic on very important parts, too much focused on graphlab

교육 기관: Alejandro V

2020년 11월 13일

TuriCreate is not the apropriate tool for practical Machine Learning

교육 기관: Pawan K S

2016년 5월 15일

Nice introductory course but too much dependence on graphLab create

교육 기관: Jesse W

2016년 12월 24일

It is better if allow me upgrade only when I finished this course.

교육 기관: Tushar k

2015년 11월 30일

Good course to begin machine learning with but it's too easy !!

교육 기관: Konstantinos L

2018년 1월 8일

Nice course but too easy. Assignments should be more difficult

교육 기관: Seong H M

2021년 9월 25일

Problems and files and videos not updated base on the changes

교육 기관: Felipe A S S

2021년 1월 23일

The libraries used on the course are a little bit unsopported

교육 기관: Nadeem B

2021년 7월 27일

Concepts and explanation is great but using outdated modules

교육 기관: Atharv J

2020년 9월 14일

The course should be taught in pandas rather than graphlab.

교육 기관: Max F

2016년 1월 10일

Not a bad course, but extremely basic. Was expecting more.

교육 기관: Adrien L

2017년 2월 2일

No good without the missing course and capstone projects

교육 기관: Himanshu R

2020년 4월 16일

It uses turicreate which is not available for windows .

교육 기관: Aleksey C

2016년 12월 11일

....mmm fsdfg gsgsd sgsdgsdg sdsdgsdg ggsgsd sgdsdgsg

교육 기관: HITESH D

2020년 6월 15일

Installing software parts gave me a very hard time.