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Machine Learning Foundations: A Case Study Approach に戻る

ワシントン大学(University of Washington) による Machine Learning Foundations: A Case Study Approach の受講者のレビューおよびフィードバック

4.6
11,515件の評価
2,757件のレビュー

コースについて

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....

人気のレビュー

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.

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

フィルター:

Machine Learning Foundations: A Case Study Approach: 76 - 100 / 2,676 レビュー

by 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

by 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.

by 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

by 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.

by Jefferson N

Feb 13, 2019

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

by 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.

by 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.

by 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.

by 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.

by 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.

by Daniel J

Jan 07, 2017

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

by Keith P D C

Oct 28, 2019

Two stars because of GraphLab! Otherwise great concepts!

by 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.

by 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.

by 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

by 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 ... :-(

by 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.

by Krupesh A

Feb 15, 2019

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

by Shreyash N S

May 20, 2020

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

by Japman S

Jun 07, 2020

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

by Youngmin C

Sep 06, 2019

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

by Darren R

Oct 13, 2015

Thoroughly disappointed to see this course based on

by Kaushik M

May 01, 2016

Too many videos and not cluttered assignment codes

by 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.

by Tim J

Jan 09, 2016

Excellent overview course. It has exactly the right balance between explaining Machine Learning concepts, and providing enough supporting mathematics & logic to understand why these concepts are correct (without going through epsilon-delta proofs).

Having followed several Machine Learning courses, this is now definitely my favourite new course, replacing Andrew Ng's famous course here on Coursera (which was also very good & especially complete, but required too often a leap of faith - this course provides really more details on the "why"). Furthermore, the exercises in this course are spot-on: they use Python and GraphLab Create (for which you get a 1 year student license when taking this course) - the big advantage is that you can focus on the Machine Learning aspect, and not on how to implement something in Python (or Matlab or R). The exercises are challenging enough and require some thought, exactly what they should do. This is not a "look up the right answer in the slides" course when it comes to exercises, which I particularly like.

The chemistry between the teachers is also very nice and shows they just love Machine Learning, and love teaching it (which they do very well).

If you some familiarity with statistics (a bit) and mathematics (a bit of matrix & vector calculations), and want to understand what Machine Learning is about, then this is THE course for you.