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

4.6
9,110개의 평가
2,174개의 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 2,093개 리뷰 중 126~150

교육 기관: Zachary C

Apr 30, 2017

A great primer on the various high level concepts in machine learning and some general applications as well as good quick intro to graphlab create. I was originally apprehensive to use another data science tool outside of panadas, but now think graphlab create is even better.

교육 기관: Pavel K

Aug 05, 2016

A very clear and straightforward course giving a foundation for the following learning of Machine Learning.

교육 기관: Omar M

Feb 28, 2016

Excellent course! I loved it! Good overview on machine learning

교육 기관: Kyrylo S

Dec 28, 2015

Excellent presentation of material

교육 기관: Dheeraj A

Jan 03, 2017

Excellent Course.

교육 기관: Josue S

Sep 17, 2017

Excellent course

교육 기관: Anindya S

Jan 02, 2016

Dr. Carlos Guestrin and Dr. Emily Fox are amazing. Needless to say, their way of teaching is absolutely brilliant and fun to learn, concepts which took me few days to learn now takes an hour or so, this is primarily due to their mastery on the subject matter and their lucid way of teaching.

교육 기관: Bhawani S L

Nov 03, 2015

Very good course to start Machine Learning Basics. Excellent coverage of practical programming assignments.

교육 기관: Andrey N

Jul 30, 2017

Great course! It can be even better if taught using scikit-learn.

교육 기관: Liliana R

Jan 22, 2016

It is a great course to learn the fundamentals of Machine Learning, also Emily and Carlos are excellent tutors, they explain very well and they give good examples.

교육 기관: Edmilson F d S

Dec 13, 2015

Excellent!! This course gives a nice introduction about Machine Learning.

교육 기관: Ouanis S

Nov 09, 2016

Excellent course, I particularly appreciate how concepts are introduced with examples to set the terrain for the consequent courses. Will definitely recommend.

교육 기관: William G

Nov 02, 2015

Outstanding!!! Can't wait for the next course on Regression!

They found the perfect balance between making it fun and challenging. Great job!

교육 기관: Rubens P

Oct 20, 2015

Good examples and very practical!

교육 기관: Chengcheng L

Dec 28, 2015

This is a wonderful course to get you into the door of machine learning. It covers several key concepts in ML. The videos are easy to follow. The assignments are not difficult to complete if you do the "follow along" exercises. You won't be able to understand the theoretical background of the algorithm very well after taking this course, but you can apply Grahphlab functions to whatever data you have and generate quick and dirty results.

교육 기관: Pasquale G

Feb 18, 2016

It's a great course. The adoption of ipython notebook is amazing

교육 기관: Nirdesh D

Jan 09, 2017

Great course. This course is designed to make it easy to learn and implement various machine learning algorithms and techniques.

교육 기관: Eik U H

Jun 27, 2017

A real breathtaking great course about the basics of machine learning with very concise materials. Unfortunately died after four parts. I'am hoping for resurrection with a part 5 and 6.

Thank you very much.

교육 기관: Mayur J

May 28, 2016

I am really liking this course as the instructors are teaching the concept just not theoretically but building a foundation by practical samples and assignement.

The course series is well designed, firstly by this course you get feel of what machine learning is and where all you can apply the concepts. Starting with all the types of ML concepts instructors are building interest among the students.

I would recommend this course to all serious students who want to get into the world of ML.

교육 기관: Dinesh P

Jun 28, 2016

This course fulfills its promises. Foundations and relevant tools are introduced via case study. Both theoretical as well as practical reviews are done before leaving for next topic. All in all, good introductory course.

교육 기관: Miguel A P L

Nov 28, 2016

Before taking this course I would not consider the topic as something that one could learn by himself.

The Course has opened my mind and has showed me that there is a lot to learn and study in order to fully master ML and AI in order to use it in the applications we can build.

교육 기관: Namit K

Apr 25, 2016

excellent introduction and practical application domains.

교육 기관: uday s

Aug 01, 2017

Great curse for anyone wanting a high level over view of machine learning. Had good mix of tutorials and quiz as well as homework. The faculty were very good and kept up the interest with some good hum

교육 기관: Ziliang W

Oct 16, 2015

Fantastic course, the professors are awesome, the assignments are great, cannot wait to see the upcoming following courses.

교육 기관: Anderson M d S

Jul 24, 2016

The course is really awesome. Of all the introductory Machine Learning courses I've taken, this is one is the best!