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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

9,861개의 평가
2,366개의 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


Dec 20, 2016

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.


Oct 17, 2016

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

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,290개 리뷰 중 2026~2050

교육 기관: Jjclof

Oct 17, 2016


Good teachers.

But a bit too simple. 4/5


교육 기관: Markus M

Feb 10, 2016

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

교육 기관: Dai W

Jan 03, 2016

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

교육 기관: Lena M

Dec 22, 2015

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

교육 기관: Andrew G L

Aug 05, 2017

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

교육 기관: Wangjun

Dec 29, 2016

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

교육 기관: Alain C

Feb 15, 2019

Technical setup is not easy, but great business cases.

교육 기관: SATYA P A

Apr 29, 2020

its was very useful to learn about machine learning !

교육 기관: Rajeev R

Oct 01, 2019

wonderful experience. It's like doing a live project.

교육 기관: Abdulrahman M A K

Jul 10, 2019

Awesome instructors and great knowledge and practices

교육 기관: Divya v M

May 29, 2016

Great overview and broad foundation of all techniques

교육 기관: Jorge S N

Apr 09, 2016

El más intuitivo curso de ML que he visto en Coursera

교육 기관: Bhakthavatsala R

Jun 16, 2018

Interactive and very interesting. good for beginners

교육 기관: Fenjin W

Apr 15, 2016

Great course! Hope the slides gets better annotated.

교육 기관: Yagyansh S K

Dec 03, 2016

Awesome Teaching Technique Used! Kudos To The Team!

교육 기관: Avinash P M

Dec 13, 2016

Assignments could have been little more difficult.

교육 기관: 吴青

Dec 06, 2017

didn't reach my expectation but still quite good.

교육 기관: Albert Z

Feb 06, 2016

Hands on should have been more involved/dificult.

교육 기관: Gopinath T

May 14, 2019

Well structured course with detailed explanation

교육 기관: A S P

Jan 16, 2018

A bit light on details but a great first course!

교육 기관: Qishen S

May 25, 2017

A good overview of ML and tutorial for graphlab.

교육 기관: Harsh R

May 18, 2020

The course is little bit outdated.

please update

교육 기관: Md S H

Nov 18, 2018

A must do course to start with Machine Learning

교육 기관: Steve K

Jan 21, 2019

great class to learn machine learning hands on

교육 기관: Spike Y

Nov 30, 2017

I like the explaining about ipython notebook !