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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
11,707개의 평가
2,805개의 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 2,718개 리뷰 중 76~100

교육 기관: Mohamed A E

Jun 06, 2020

the course concepts were good but as everyone is saying the materials are outdated and you use TuriCreate instead of GraphLab so you have to search for the appropriates functions some times, and the installation was hard too because TuriCreate works only on Linux or WSL, I almost quit the course because I couldn't install it at first

교육 기관: Nik M N N G

Feb 11, 2020

The material in this course severely needs an update. Some of the code examples (not from the video, because the video is obviously from old materials) are problematic. It's an interesting experience to learn a new library but I wish the experience is different. The quiz should be tougher in my honest opinion.

교육 기관: Jaime R

Dec 17, 2018

Great introduction course. However, getting the notebooks to work with Graphlab is a real pain. The notebook exercises are also mostly make-work rather than real explorations. The explanations and the notebooks themselves are pretty good though

교육 기관: Ayush G

Jun 06, 2020

the course seems outdated in many aspects, the support isn't available to clarify doubts and the documentation isn't updated either. Moreover, the software support has ended.

교육 기관: Jefferson N

Feb 13, 2019

A good course, but the tools are a bit dated and it's showing its age.

교육 기관: Craig G

Aug 05, 2020

It is interesting, but turicreate isn't compatible with current version of python (3.8) and there's little/no support as the forum is not curated and not much student interaction. The problems seem to be only loosely related to the material. Many questions in the problems aren't discussed in the lectures and turicreate isn't widely used so it is difficult to find explanations or clues on how to proceed.

교육 기관: Malik M W

Mar 31, 2020

I think this course is outdated as they are using python 2 also the platform they use for machine learning only supported by python 2. Due to these limitations, I too was unable to continue this course. Because every time you have to work with new libraries you have to uninstall python 2 and reinstall python 3.

교육 기관: Vakkalagadda A r

Dec 28, 2015

Instructors or TAs are not available in discussion forums. and the course is focussed on promoting "graph lab" proprietary package of the course sponsor. Maybe you can have a look, not beneficial if you are serious about learning ML.

교육 기관: Ujwal A

Mar 27, 2020

This course has used windows OS and application built for it. But the library/application is no longer supported on windows. So this is really a big problem for windows users.

교육 기관: Joseph C

Jul 29, 2018

Overly relies on a paid software (free for the course) called GraphLab. The course can be completed without GraphLab, but expect little / no responses to questions.

교육 기관: Daniel J

Jan 07, 2017

excessive use of GraphLab create which is not an industry standard.

교육 기관: Keith P D C

Oct 28, 2019

Two stars because of GraphLab! Otherwise great concepts!

교육 기관: Vishok

Oct 12, 2020

IF you are a beginner who would like to take up a job in a Data Science related field, read on:

The packages used here are not listed in a single job requirement in Angel, Glassdoor, etc. I know they said use the tools you want to, but most people taking up courses like this or similar are people with none or limited experience in Machine Learning. Rather than promoting tools created by the professor (Turi; Read the Wikipedia page, it seems like an advertisement) they need to use tools that are widely used in the industry.

(Though Turi has been acquired by Apple, the scope is very limited)

Furthermore, due to lack of proper support and solutions on sites like Stack Overflow, it gets harder for a person who lacks programming experience to debug if any problems arise

**THE BIGGEST ISSUE: Turi is NOT SUPPORTED on Windows!** I had to use a virtual environment in Ubuntu Terminal. (I may be wrong with the exact wording) For finding out how to use the package read this:

https://blog.usejournal.com/installing-turicreate-on-windows-10-534e147a4792

(Funny thing, the author of the page actually wrote "If you are taking the Machine Learning Foundations: A Case Study Approach", meaning someone would rarely use it for anything else IF they do)

Concept Explanation was good, but the above point was a major disappointment because I had to learn packages like Pandas and Scikit-Learn (Any job listing on Machine Learning using Python would list these as a MUST requirement. Besides, the support available on Stack Overflow is huge) after learning a package I would never use in my job.

So my suggestion is if you don't mind learning Turi and would like a surface level explanation of the concepts, go on.

교육 기관: Mihir I

May 13, 2020

Extremely disappointed with the quality of the teaching content. There is a major disconnect between the materials presented in the videos and quizzes. While there is a warning that there has been a shift from graphlab to turicreate, there is no way to assess the impact on additional effort required to fill in the gaps. In fact, one of the instructions in the week 2 programming assignment is outright wrong so you will be able to pass quiz. The discussion board is tough to navigate because of the subject heading are cryptic e.g. Need help, Error, etc. As a result one has to sift through many post to get an answer. Compared to other offering on Coursera, It is not worth paying for this course.

교육 기관: Peter F

Mar 30, 2020

This course would be okay if it weren't for turicreate, a Python package that's supposed to simplify things. If you have Linux or a Mac, it will do just that, but if you have Windows steer well clear of this course. The lecturers haven't considered the possibility that anyone might not have Linux or a Mac. All the faffing around getting turicreate to work (I did it once and I'm not doing it again) wasn't worth my trouble so I ended up guessing the answers to the quiz questions (you're allowed three attempts every eight hours) just to get this course out of the way. I'll use something actually accessible for the remaining courses, namely R.

교육 기관: Rithik S

May 26, 2020

The files that are given in readings are unable to open and turicreate cannot read that files also. I cant complete my assignments without reading those files. They haven't given any detailed explanation about how to read those files. In videos they had explained through csv files but in assignments they had given sframe file which are unable to read

교육 기관: Jitendra S

Apr 29, 2016

Dato tool does not even install properly.. so n´makes no sense to continue with the course. The support team fail to help in installing ... :-(

교육 기관: Ashutosh N

May 30, 2020

The course is explained using turicreate , which does not work in windows properly. It should have been explained using open source libraries.

교육 기관: Krupesh A

Feb 15, 2019

Uses very old versions of libraries. Many students are facing issues which remains unsolved. Not recommended to pursue it.

교육 기관: Shreyash N S

May 20, 2020

graphlabcreate creates many problem while working..it should be changed

교육 기관: Japman S

Jun 07, 2020

Based on Python 2 libraries not working on python 3. Obsolete Course

교육 기관: Youngmin C

Sep 06, 2019

Too old, bad packages, not much to learn. too basic.

교육 기관: Darren R

Oct 13, 2015

Thoroughly disappointed to see this course based on

교육 기관: Kaushik M

May 01, 2016

Too many videos and not cluttered assignment codes

교육 기관: Ryan C

Aug 22, 2016

This course is excellent for anybody new to machine learning and wanting to learn this new skill from the top down. For me, I have a strong background in machine learning, not in the context of big data, but I wanted to get familiar with Python and learn how modern companies are using machine learning in practice. This course provides that applied approach to implementing a broad range of machine learning applications with Python, applied to real problems.

A course this small cannot provide everything - what this course does not provide is in-depth technical tutorials on the workings of machine learning algorithms. There are many courses out there which do, but this course to great for learning a practical approach to problem solving with machine learning and data processing.

If there is a downside, I would say that the use of paid packages in the lectures (graphlab) limits the student's ability to learn Python using the freely available packages on the web, which was my personal preference. However, this is not purely negative, since there are many employers out there who would like to know that you have practical knowledge of things like AWS and graphlab. I did enjoy learning about those packages and services and I feel like I learned something positive which I can share with potential employers.

Overall, a very good concise course - one of the best on Coursera for vocational learning in my opinion.