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Avis et commentaires pour d'étudiants pour Machine Learning Foundations: A Case Study Approach par Université de Washington

4.6
étoiles
13,022 évaluations
3,098 avis

À propos du cours

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....

Meilleurs avis

BL

16 oct. 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

PM

18 août 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.

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2951 - 2975 sur 3,022 Avis pour Machine Learning Foundations: A Case Study Approach

par Charan S

16 juil. 2017

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.

par Eiaki M

5 mars 2016

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.

par Robert P M

27 oct. 2015

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.

par Kishore Y

25 sept. 2021

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.

par Evlampi H

5 nov. 2015

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!

par shanky s

26 avr. 2021

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

par Simone V

21 avr. 2022

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

par Piotr T

6 oct. 2015

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

par David F

2 déc. 2015

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

par Patryk H

14 oct. 2015

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

par Elgardo E

29 mai 2020

Course videos are outdated and requires time to investigate and research.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

par David H

31 oct. 2015

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

par Zuozhi W

7 févr. 2017

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

par Suhasini L

4 sept. 2020

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

par ashish s g

15 févr. 2017

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

par Mark F

19 déc. 2015

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

par De V d P

13 mars 2022

outdated nightmare to get started. unusable practicals outside of learning sand box.

par Najmeh R

4 oct. 2016

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

par Jason S

24 août 2021

great professors, great setup. Just extremely outdated software is used.

par tiafvoonug k x

6 janv. 2016

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

par Ishank C

6 juin 2020

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

par Satyam N

26 mars 2018

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

par Paolo G

18 avr. 2021

This course has no value!!! it's using obsolete tools.

par Mohamed T K

26 juin 2020

Too hard

par Richard M

4 juil. 2021

I​ would avoid this course. The course structure is badly organised and hard to follow, the material covered is lacking in detail on key underlying concepts that are key to learning what you're doing and the notes provided do not provide key information that would let them be used as reference material for you to go back and review.

B​ut - much more importantly - the course notes and information have been written using an old, out of date, library, while the tests and some of the material refers to a newer library that is not a direct replacement. As a result, many of the instructions and guides don't work at all, or are incredibly hard to understand with the new model.

F​inally, also as a result, many of the test question's answers are wrong - when you do the questions using the new library you get an answer that the automatic grading says is wrong - even though it is correct.

A​nd there is no help in the dicusssions from moderators.

S​o while this may have been a passibly acceptable course at one time, it is now basically a frustrating, bi-polar mess, with no help provided to guide you.