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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
9,970개의 평가
2,389개의 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

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.

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

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,307개 리뷰 중 201~225

교육 기관: Wilfrid L

Jan 08, 2019

Very good course, I enjoyed the way the instructors structured and presented the material, in both a professional and personable manner, and the use of case studies to help solidify the knowledge. Assignments were very well built; although they used quizzes, it really required some thinking and prep work to get the answers right.

교육 기관: Sunil K

Jun 23, 2017

This course has excellent content which is very relevant to Machine Learning practice in industry. However the assignments are little easy. I think this is because this is a case study approach and like an introductory course. I would strongly recommend this course for a beginner who want to learn how ML is being used in industry.

교육 기관: Tinsae G A

Sep 24, 2016

It was very nice experience. Prior to the course, I heard about most topics. This course helped me to structure the ML concepts in my mind. I like learning by doing. The assignments in the courses really challenged me and I learned good practical knowledge. I am a beginner to MOOC courses, this course was a good start. Thank you.

교육 기관: Luigi P

May 15, 2020

It's a great course as first approach to this fantastic world "machine learning". It provided to me a general overview about the potential and the state of art of that technology. This course fired up my curiosity to "deep learn" about mathematical concept behind the scenes and I very hope next courses can cover that knowledge.

교육 기관: DIONYSIOS Z

Oct 02, 2016

One of the best courses that I attended so far in Coursera. If you already attended the Machine learning course from Andrew Ng or you have some idea of what is Machine learning about, this is the perfect next step. Explanations of machine learning 'buzzwords' and real python examples. Instructors are great. Highly recommend it!

교육 기관: Mubbasher K

Jan 28, 2018

Excellent course, really appreciate the your hard work in creating easy to follow course, very good slides and presenting information and explanations step by step.... oh and also love the on-screen chemistry between both of you and engaging style with students. It has been an enjoyable course. Please keep up the good work.

교육 기관: Alejandro V

May 12, 2017

This was a great introductory level course to machine learning. It was very practical and allows for one to really start employing ML techniques quickly without getting too bogged down by theory. It was a pleasure working in Python and with GraphLab for this course. Looking forward to the next courses in the specialization!

교육 기관: Steven R

Jun 06, 2016

I learned a lot from this Machine Learning course! It was rather general, but that was what I expected from the first course in the series. In my opinion it was worth the money as the quality was high and it provided an extremely good starting point in this area. I'll definitely be purchasing the next course in the series.

교육 기관: Renato P

May 29, 2016

Great course. I really enjoyed going trough all the classes with Emily and Carlos. The case study approach is also very compelling. Loved it and really recommend it to anyone curious about ML.

Some previous experience in Python is required, which I hadn't, so I had a quick Codeacademy python course that really worked well.

교육 기관: Prem S

Feb 01, 2016

Got the best course so far to introduce me to the concepts of Machine Learning. Kudos to the instructors Emily and Carlos for providing a well laid out syllabus with an approach that was grounded on practical concepts and demonstrating hands on with real world examples. Hoping and requesting them to keep up the good work.

교육 기관: Giovanni

Sep 14, 2018

This course offers a broad range of examples in ML. Clearly some basic knowledge of linear algebra and other concepts is needed, but I believe it is well structured to help those who're not so strong in math. It really is basic, though, so if you have already some knowledge in ML this will result sometimes a bit slow.

교육 기관: Layne C

Oct 30, 2015

This is a very good introduction to ML. I felt that everything was presented in a very straight forward manner. A little more guidance on installing python and jupyter would be beneficial for those that have not used python packages much.

Overall a great course and I am looking forward to the more in depth courses :)

교육 기관: Scott v K

Sep 26, 2015

Great overview and engaging introduction to regression, clustering, classification, and deep machine learning with hands-on ability to see some of these practices in action programming exercises in Python. Good introduction to the more in-depth materials which will be covered in other courses in the specialization.

교육 기관: Zheng L

Oct 24, 2019

This course is very interesting and teaches you the basic concepts and practice applications of machine learning technics. The only drawback is that this course rely heavily on graphlab package which cannot be used in Python 3.7. Took a long time to search for alternatives in sklearn instead to finish assignments.

교육 기관: Adil A

Oct 13, 2016

This is an excellent course... One can tell that a lot of effort went into making this course fun and easy to work with... Almost certainly the most fun to work on course I've taken on Coursera so far... The instructors are very nice, the video lectures are fun and the assignments are easy and fun to work with...

교육 기관: Vijaykumar G

May 08, 2020

It was greate and complete foundation course on ML which i have taken by University of Washington department. The lectures are very clear and can adopt to the real world problems. i am very much thank full to the faculty for such an wonderfull case study approches given in the entire course.

thank you once again.

교육 기관: Fakrudeen A A

Aug 05, 2018

Excellent course and highly recommended - covers fundamentals, TF-IDF, cosine. jaccardian similarities, recommender systems (precision/recall, AUC), deep learning via transfer learning (not having to explicitly build a model for the problem).

Exercises could be done in some tool which is common across industry.

교육 기관: Bola M

Jul 19, 2016

Awesome course! Only gives an introduction into the Machine Learning topics but does it well. As a Technical PM in the software industry, this was enough depth for me to understand the basics of machine learning algorithms. Also has good hands-on tutorials with Python to implement the algorithms which is great.

교육 기관: Jorge H

Nov 07, 2016

Excellent course!!... It has been the best online course so far. I really enjoyed the Use Case approach, and got really excited with the fact that –although being an introductory course- I got really a good intuition and hands-on experience about use of machine learning for real applications.

Congratulations!!

교육 기관: Carol V

Feb 27, 2017

This course helped me develop a good understanding of complex machine learning concepts.

The tools were easy to use and helped me learn quickly. Unlike other programming classes I've tried in Coursera, I did not have to deal with programming environment related problems. I learnt important python skills also.

교육 기관: Baranitharan S

Apr 14, 2018

The course sets a strong foundation for someone who wish to specialise in the AI and ML space. The course content is easy for a beginner with a very little or no (you gotta believe it) software coding background. The instructor are awesome and help you to go thru the course with ease and not getting bored.

교육 기관: Srividya N

Nov 01, 2017

There is so much of flexibility. It is so cool and so interesting... I could complete this complex course so easily with some of the key activities like below:

Exercise videos

taking quiz questions multiple times with no penalty

simple English and explanation of complex information in simple and easy terms

교육 기관: Walid O

Mar 04, 2017

this is course is very good for a beginner who wants to know what is machine learning , why we want this , what is its application .

also you will understand many algorithms used to manipulate data to do very cool applications and you will do this yourself .

they made it very easy to understand , thank you .

교육 기관: Xiangwei C

Jul 09, 2016

It is a very well structured and effective course. I really learned a lot of machine learning techniques that I can use immediately. Both instructors did great job explaining the concepts and algorithms. Very powerful python tools are introduced, and I love them! Definitely worth the money that I paid for!

교육 기관: Gaurav S

May 20, 2020

Emily and Carlos have done a great job in preparing this course. This course is for anyone who doesnt have any background of Machine learning. The hosts have taught the course by implementing a practical approach. I have learnt a lot out of this course and i hope to complete the remainder of the courses.