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

4.6
9,097개의 평가
2,170개의 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

BL

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

SZ

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.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,089개 리뷰 중 151~175

교육 기관: Lan J

Nov 02, 2018

Love it. Easy and useful.

교육 기관: Sunil B

Nov 02, 2018

Very detailed and covers the fundamentals well.

교육 기관: SOUVIK D

Nov 05, 2018

awesome course. 100% recommended for beginners. I just loved it. Thanks to Coursera for providing such courses.

교육 기관: Muhammad A

Nov 05, 2018

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.

교육 기관: Kripakaran R

Nov 10, 2018

Some of the informations are half baked, hope to see them in future classes.

교육 기관: Ankita M

Nov 20, 2018

great content and good exercises

교육 기관: Pavan B

Nov 20, 2018

What an amazing way to start the course. After first module, we know a little bit about every specialization topic. Great material.

교육 기관: José A S P

Oct 19, 2016

awesome! fantastic! outstanding!

교육 기관: Xiuyuan C

Jan 16, 2017

Definitely a good choice for entering the area of machine learning

교육 기관: Younghwan K

Dec 24, 2016

Ex

교육 기관: Jonathan C

Oct 26, 2017

learned some really amazing things in this course!

교육 기관: Nand B P

Jun 27, 2017

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.

교육 기관: Navinkumar

Feb 09, 2017

Its goo

교육 기관: LEPAGE

Mar 14, 2017

As a statistician, Excellent introduction to ML!! I can't wait doing the other specializations (regression almost done, clustering and classification on-going

교육 기관: Vinod T G

Aug 14, 2017

Excellent course for folks who need to understand ML and how it can be used in an array of day to day applications

교육 기관: Mark h

Jul 07, 2017

very helpful for a totally new learner

교육 기관: 任晨熙

Jan 28, 2017

很专业,正在学习

교육 기관: Sourav K R

Sep 09, 2017

Best courser for machine learning basic understanding.

교육 기관: Shivam A

May 10, 2017

Amazing for beginners.

교육 기관: Massimiliano C

Jul 22, 2017

very good course, complex topics explained through intuitive and practical use cases, in short time provides an overview on Machine Learning and gives the student the chance to go in depth if necessary.

I liked it very much.

교육 기관: TAMERA Y

May 16, 2017

Really enjoyed the course. This was a great course for someone who has never taken Machine Learning Or Python. I found the Graphlab Note book very helpful. Plus I loved having the opportunity to write the code / algorithms with Carlos. Great Co

교육 기관: Adam D

Jan 30, 2018

It is great course for beginners. Now I have basic knowledge about machine learning and I can go forward with next courses. Thanks.

교육 기관: Nithya B

Mar 15, 2018

useful

교육 기관: Vishal A

Nov 29, 2017

They have used graphlab instead of using standard library. But overall good course.

If the student can submit quiz question without enrolling then it would be a big plus.

교육 기관: alireza r

May 29, 2017

The best instructor ever