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

11,895개의 평가
2,848개의 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 2,763개 리뷰 중 2726~2750

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 4일

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: 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: 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.

교육 기관: Najmeh R

2016년 10월 4일

The subjectes are not learnt deeply and precisely. Too summarized and vague!

교육 기관: tiafvoonug k x

2016년 1월 6일

As a non programer, or mathematician, this course is too hard to follow.

교육 기관: Ishank C

2020년 6월 6일

They Don't tech the mathematics behind the machine learning.

교육 기관: Satyam N

2018년 3월 25일

This course doesn't give any insight about the algorithms.

교육 기관: Mohamed T K

2020년 6월 26일

Too hard

교육 기관: Raza K

2020년 4월 5일

I have a few concerns regarding this course. First of all the instructor strongly suggested that we should use python and turicreate package. I had several difficulties in installing turicreate on my mac. There was no help avaliable on the forum in this regard. Finally, I ignore the instructions and downloaded anaconda and then downloaded turicreate.

But it turns out that the instructors are not using turicreate in lectures but graphlab package. Moreover, the instructors using python 2.7, which has a different syntax than python 3.

This made learning much harder and frustrating.


2020년 5월 30일

Hi there , I have find difficulty in completing the course, the packages that are used in python are outdated, or that are used in python 2 version like turi create and sframes,, as for now I have python 3 version , so i find difficulty to undustand the coding discussed in the course., or they can use pandas or scikit packages for more convinence, for getting upto date i am sorry, that i have decided to not learn the course

교육 기관: Rangarajan m

2020년 8월 30일

Not focusing on Basics of Machine Learning rather to focus on specific software application on Turi . Unable to complete the quiz which is based on non-user friendly Turi software installation.

Please be generic and encourage to use Jupyter Ipython notebook to use common libraries to focus on Machine Learning basics not to promote Turi or specific software to complete the course

교육 기관: Vilasha V N

2020년 4월 11일

Not worth doing. Notes are insufficient to help install packages needed to follow the course. Many had posted on the same error message but there has been no guidance. Support is very poor, Course materials are outdated. Not recommended.

교육 기관: Kyle D

2020년 7월 9일

The software was so difficult to install. It did not seem worth it to learn a completely new way. Unfortunately, I dropped it because the case study approach looked interesting.

교육 기관: Sahil K

2020년 11월 23일

Software installation was a big trouble and took nearly month as this course was in graphlab, but we need to use turicreate or other toolset.

교육 기관: Kunal

2020년 9월 21일

its very very hard to setup jupyter notebbok and installing turicreate ,also takes a lot of efffort in practical quiz