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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
12,657개의 평가
3,030개의 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
2016년 12월 19일

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
2019년 8월 18일

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 2,949개 리뷰 중 2751~2775

교육 기관: Troy D

2020년 2월 5일

Good course, learned a lot of basics. I think this course is rather old though and getting a lot of the required software up and running required a lot of work since there are much newer versions available now. I found that I had to do a little extra to get the older packages working in Jupiter.

교육 기관: Aleksandar S

2016년 5월 25일

The course content is great. It gives overview on what is going to be learned in details in the next courses. Considering that it is an introductory course and the fact that it utilizes the GraphLab library as tool, I believe it is overpriced compared to the other courses of the specialization.

교육 기관: Yaniv S

2017년 1월 15일

The whole eco-system is based on Graphlab create which is not very commonly used in the industry. The "Programming assignments" are very much like the exercise done in the videos - so no real thought and effort were needed. The Deep learning part is really bad thought and bad examined.

교육 기관: Eric J

2016년 7월 12일

The enthusiasm of the instructors was the best thing about this class. But I really wanted a more rigorous methodology - and didn't really get it here. But it was an alright introduction to machine learning but not enough if you want to know what makes the 'black box' work.

교육 기관: Paulo S B d O F

2016년 9월 5일

Pros:

(1) Teachers know what they are talking.

(2) They are energetic and funny.

Cons:

(1) The course uses proprietary and expensive tool.

(2) The course is too simplistic.

(3) The teachers, although they know what they are talking about, they aren't very good at teaching.

교육 기관: Anirudh A

2021년 2월 26일

Good with concepts. But would have been better if a standard library like scikit were used rather than SFrames, Turicreate and Graphlab for the sake of easing things out which actually is not very convenient for a lot of students. (atleast during the learning cycle)

교육 기관: David K

2016년 3월 1일

I think that the course is redundant, it is to general, trying to capture to much, and using a commercial program tool that's doing to much behind the scene.

The second course in the specialization is really great though and you wont miss anything if you skip ahead

교육 기관: Varun J

2015년 9월 24일

A lot of problems with software installations. But, the professors for this class seem to be very passionate about the course and they teach well. If not for a lot of problems faced during software installations(which is still not resolved), would have given 5 stars

교육 기관: Michael C

2016년 4월 10일

Really just an overview of the topics to be explained in detail afterwards.

Big plus for the use of python + notebooks but otherwise, if one is interested just in the overview and not in all the specialization, maybe the Andrew NG course is more detailed.

교육 기관: Bernardo C

2016년 6월 8일

El curso tiene mucho potencial, pero hay que afinarlo.

Pienso que los vídeos deben ser reeditados. Tienen errores y conceptos confusos. Deberían ser tan claros como para lograr tomar buenos apuntes y usarlos en las tareas. Las tareas son casi mecánicas.

교육 기관: Rishi H

2019년 6월 11일

Content and material is good and the trainers are good. Only issue i found is course assignments are heavily dependent on Sframes and graphlab which does not work most of the times.,they should go with panda libraries which is easily accessible.

교육 기관: Aman S

2018년 6월 14일

The worst thing about this course is graphlab. Trying to run it since last 10 days with the help of every available online resources, but in vain. There are many flaws in graphlab. I tried a hundred times to view images in graphlab, but in vain.

교육 기관: Juarez B

2017년 1월 12일

This course introduces the key topics of Machine Learning, but the math behind the algorithms is not explained and the programming exercises are too easy. Unfortunately, it also relies heavily on graphlab instead of using open source software.

교육 기관: Mohit S S

2018년 8월 7일

Course contet is ok. But, intructors really need to teach in a platform neutral way or some other popular library for which ample support is available. In my opinion, learning a tool which is nowhere used in te industry is not a good idea.

교육 기관: Tarek M s

2017년 11월 5일

the course is good for starter but according to its repetition I waited more .

one star down for many useless information in lectures about Amazon products and so on.

one star down for forcing using unpopular python library .

교육 기관: Piyush K P

2016년 10월 24일

thanks to prof and cousera for this wonderful course. I wish the programming part was taught separately from basic. I have taken the previous course which was case study approach with respect to which it was slightly tough.

교육 기관: Jerome B

2017년 12월 19일

The teachers are nice and the content is pretty interesting, but they keep talking about the Capstone that we actually won't do. That make me wonder if it's worth continuing, and wonder why they cancelled it eventually.

교육 기관: Gregory T

2016년 10월 30일

This was a valuable introductory survey course. For me, the challenge came from my unfamiliarity with Python not the material. I would rate this class as "entry level" for anybody with a college-level technical degree.

교육 기관: Brandon P

2018년 3월 10일

There were a lot of assumptions made about my math background. Terms and concepts were used that are foreign to most people and while the forums were helpful it was interesting to see that this is a common feeling.

교육 기관: Mohammad A

2019년 7월 22일

Course include great knowledge, but when coming to work on tools, they are using old method like we have python 3.7, but course is going through python 2.7 and also older version. That's creating confusion somehow

교육 기관: Ivan P

2016년 5월 6일

It's not a bad course, but it forces students to use GraphLab, a framework created by one the professors teaching the course, instead of using scikit-learn, a widely used framework for machine learning in Python.

교육 기관: chris s

2016년 1월 27일

This course has so much potential but is based on proprietary software. The instructors are excellent and the content is really good. It would get 5 stars if it was based on all open source software.

교육 기관: Nishant K

2020년 10월 31일

Great approach with basic explanation of applying and importance of the domain in read world examples. Could have been more in depth in few areas but hopefully will be taken care in following courses.

교육 기관: AHMED E A

2020년 7월 23일

The course needs to be updated....I have hard times installing turicreate and graphlab on my laptop... at the end, I had to use google collab....

I guess this course needs to use tensorflow instead...

교육 기관: Luis F A C

2020년 12월 5일

Aprendí muchas cosas interesantes. Actualmente es grande la dificultad para realizar las prácticas de programación con la librería que usan "graphlab" la cual no se relaciona my bien con windows.