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

13,053개의 평가
3,105개의 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


2016년 10월 16일

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


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 3,032개 리뷰 중 2951~2975

교육 기관: Matthew F

2019년 7월 21일

Focused too much on graphlab as opposed to the ML. If the course was titled ML with GraphLab I wouldn't mind (and wouldn't have signed up). The gaffs are kind of charming but really I would expect some of the videos to have had another take or two.

교육 기관: Joseph J F

2017년 8월 20일

It is more a course in using the tools designed by the teachers than machine learning. It might do something for a less experienced user in programming, but I didn't find it much use. The overview of Machine Learning tasks isn't bad.

교육 기관: Andras H

2020년 5월 31일

on one hand good... on other hand annoying ( mixing graphlab and turicreate... shitty wording of the assignment task, info added as side note which was vital for the assignments...etc.) The curse material would need a refresh.

교육 기관: Sunil T

2020년 5월 24일

SFrame data do not support by an updated version of the Python, so student won't able to finish their assignments. So instructor need to update the materials and database which is supported by a new version of Python

교육 기관: Tudor S

2018년 4월 22일

The Assignments and Quiz questions are hard to read and comprehend.

Although individually the course presentations are ok, overall this course isn't a very relevant or coherent introduction to Machine Learning.

교육 기관: Taylor I

2020년 5월 11일

Feel like I have been duped in a way. No capstone project and you are pretty much forced to use Turi Create (proprietary/black-box version of pandas), which I found incredibly hard to install and use.

교육 기관: Ashley

2019년 6월 23일

Content is outdated and should be revamp, the library use in this course is only for python 2.6 which is legacy and should be updated to latest python version using skicit learn instead of graphlab.

교육 기관: Arman A

2016년 2월 16일

The course uses proprietary tools for machine learning and data manipulation, making it effectively useless! However, the material on describing the machine learning algorithms were excellent!

교육 기관: Annemarie S

2019년 5월 24일

The instruction conceptually is fine, but I really disliked dealing with setting up Graph Lab Create and SFrames when we could have instead been using more commonly used open source software.

교육 기관: Charan S

2017년 7월 16일

If someone is looking for ML foundations and what is ML, they can choose this course. This is very basic course and i feel should be excluded from the ML specialization.

교육 기관: Eiaki M

2016년 3월 5일

One would learn a thing or two, but the course is very sparse compared to other machine learning courses, and I didn't feel that it was worth the time and the cost.

교육 기관: Robert P M

2015년 10월 27일

I do not like this course being tied to a commercial product. In my opinion it should be using an open source python library and not focusing on the Dato product.

교육 기관: Kishore Y

2021년 9월 25일

This is a good idea to use the case study approach. However, there are issues with files and program setup that stopped me from continuing with the course.

교육 기관: Evlampi H

2015년 11월 5일

The framework is ok, but it would be more insight on the functions would be much more amplifying the learning process.

Good working examples, though!

교육 기관: shanky s

2021년 4월 26일

I thought that indepth will be taught and enrolled for this course, but unfortunately its only basics. I wasted my enrollement

교육 기관: Simone V

2022년 4월 21일

It started nice but there are some basic aspects, like installing Turi Create, neglected. I had to withdraw from the course.

교육 기관: Piotr T

2015년 10월 6일

it's rather a course on using API of proprietary software with very very basic background on the actual math underneath

교육 기관: David F

2015년 12월 2일

I didn't like the python environment, I thought it will be more like Ng's course. Nice explanations, but for amateurs.

교육 기관: Patryk H

2015년 10월 14일

Due to many technical issues with GraphLab lib I have to reduce acitivity in this curse for only video viewing :(.

교육 기관: Elgardo E

2020년 5월 29일

Course videos are outdated and requires time to investigate and research. This causes wasted time and effort.

교육 기관: David H

2015년 10월 31일

Very, very high altitude introduction presented in a seemingly confused way with a lot of product placement.

교육 기관: Zuozhi W

2017년 2월 7일

TBH this class's experience is not good. The lecturers seem unprepared and they talk very repetitively.

교육 기관: Suhasini L

2020년 9월 4일

Not given details like what is a vector? people from non technical backgrounds will have tough time

교육 기관: ashish s g

2017년 2월 15일

Very good course material. However, Graphlab is no longer free to use for commercial purpose.

교육 기관: Mark F

2015년 12월 19일

This course is to much about graphlab and not enough about the mechanics of machine learning.