Chevron Left
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
stars
9,221개의 평가
2,200개의 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.

PM

Aug 19, 2019

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.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,119개 리뷰 중 151~175

교육 기관: A. B

Feb 29, 2016

Great course--I love the case study approach! Combined with both instructors enthusiasm for the subject, the approach was a great way to ground the theory. The quizzes & labs guided a deeper exploration into the topics the details presented in the modules.

I'm excited to continue digging into the course material while moving towards the capstone.

교육 기관: Daniyar M

Feb 17, 2016

I thoroughly enjoyed the course. I was hearing about Machine Learning so much that i decided to see whats the big buzz about, and big it was! Now i have some of the ideas for my own projects and some solutions for old problems. And must i say that the instructors are amazing, really love their job! Will definitely use graphlab in my work from now.

교육 기관: Sabarish V

Apr 18, 2018

The course is easy to follow. With the IPython notebooks that are already filled in complementing the teaching, everyone can appreciate the applications of machine learning. What's even better is that, because of the notebooks, one can see that one doesn't necessarily need to be very skilled at maths or coding to build their own application.

교육 기관: v s

Mar 24, 2018

this is pretty cool, I enjoy this course and the dynamic between the instructors. This course touched on important concepts and purposely omitted the details of the underlying math and algorithm in order to give you a bird-eye-view of the ML landscape. It also wets my appetite to learn more about the details behind the magic! Good approach.

교육 기관: Alan L

Dec 22, 2017

Amazing Introduction to ML. I came in with little understanding of ML and no Python or coding experience. I had to do most weeks twice while learning extra Python on the side from Code Academy but if a complete novice like me can do this anyone can! The professors are great- they're great at breaking down complex ideas into simple examples.

교육 기관: Bruno L

Dec 19, 2016

In this course, you use ML algorithms that are already implemented to solve various kinds of problems. The goal is to give you a broad overview of ML and how it can be used to solve real life problems.

Subsequent courses of this specialization dive deeper in each algorithm. You'll learn the theory behind them and implement them from scratch.

교육 기관: Aldo V M

Feb 25, 2019

Excellent course Carlos & Emily! I enjoyed your lectures a lot, ML is complex but you guys found the way to deliver the message clear, easy and in a funny way. Using real world examples was amazing. Guys could you let me know which other courses you are teaching? Ill be glad to continue learning from you guys. Many thanks, obrigado amigos.

교육 기관: Iurii S

Oct 15, 2017

Great course! I like their approach of describing application first and then trying to use a fairly complete approach. Submissions in the form of quizzes and auto-graded assignments work better as one does not have to wait for other people to complete the course at the same time, which might be rare at the beginning and end of the session.

교육 기관: Nelson P

Oct 30, 2017

Great introductory course to ML! I learned some valuable insights by building actual models using GraphLab. After taking this course, you'll have the foundations and overview of machine learning to take the follow up courses in the ML certification by same instructors or take any other ML course available out there. Highly recommended.

교육 기관: Rajat D

Oct 20, 2017

I really liked the case study based approach of this course. It makes you hit the ground running by applying the concepts learnt in a lesson in the case study immediately. I also like the light hearted tone of the teachers - Emily and Carlos, which helps in retaining interest through some of the more challenging concepts in the course.

교육 기관: Sivashankar G

Jul 17, 2016

This course is the right choice for someone who wants to get a high-level overview of the various fundamental concepts in machine learning and provides the zeal to pursue further. Concepts have been explained by the lecturers really well and quizzes and assignments help us to validate our knowledge of the concepts in a seamless manner.

교육 기관: Bharat R

Jul 30, 2017

This course is a great way to get adequately detailed knowledge of Machine Learning Algorithms. The approach to it (case study based) makes it so much more fun and enjoyable that you can really apply yourself to it. The professors have simplified the most complex topics and explained it amazingly well. Happy to have taken this course.

교육 기관: Mesum R H

Oct 16, 2017

A very very awesome course with exceptional explanations for each machine learning paradigms and use cases. The best thing for the course was the case study approach. I am taking this approach to train my people as well but over all thank you Carlos and Lady.. for the effort. Really hands on python and machine learning experience (Y)

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: 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.