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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
13,083 évaluations

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.

The forums and discussions were really useful and helpful while doing the assignments.

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2476 - 2500 sur 3,043 Avis pour Machine Learning Foundations: A Case Study Approach

par Andres G

9 avr. 2016

I wish they would rely in something else than a proprietary package for the course.... but besides that it's a great course.

par usman i d

4 févr. 2020

the Content was good,Instructor well explain. but at some point they need more explanation related to assignments and quize

par Steven K

20 août 2017

Takes a very soft approach, at least to start with (a little slow). Uses closed source tooling, so that might not be ideal.

par Vladislav V

27 mars 2016

The course is very simple so far. Hope it's just because it's the first one in the specialization. Love the teaching style.

par Cameron M

30 mai 2018

Good tips. A little bit of hand-holding, however, nice starter course and good introduction to a broad range of concepts.

par Khushboo K

21 avr. 2021

Good course for newbies, but hoping the coding used sklearn and other tools that are more useful in real life situations.

par hamid k

26 nov. 2019

Great course. Hope to see and update on using the libraries and facilitate the learning process for the students. Thanks,

par Sudeep K

26 mai 2018

A really nice course for someone who is new to the interesting world of machine learning and all the possible application

par ezz@winning.com

13 nov. 2015

Excellent case study approach. Hopefully, other methods-rather than graphlab- will be included as well in future courses.

par Faiza F

7 janv. 2019

Good as theoretical concepts but labs stick with Graphlab which not commonly used library. But overall good experience.

par Joseph T

11 août 2016

This course was a good teaser. Everything is very easy and fun. At the same time, you can see how powerful graphlab is.

par Diego F C d M

17 août 2020

Really good lectures, missed a bit of a complexity and got some problems with the hole turicreate/graphlab transition.

par Sunit K

30 mai 2020

Very practical course which gives you real world implementations of Machine Learning. Absolutely enjoyed the material!

par Yub B

16 avr. 2017

Pretty decent course for beginner to learn machine learning. A case study approach they used is great and interesting.

par CESAR A Q C

28 juil. 2021

T​here are some troubles with the new library but the concepts are clear and the practice was good and entertaining.​

par Neel S

30 avr. 2020

It's very good and very well understandable course. It cover core concepts of machine learing.

Thank You! Sir and Mam

par Peter W

11 mars 2016

In general a good course, well presented.

4 start only due to some assignment questions not being covered in lectures

par Kevin A

29 juin 2017

I haven't yet finish this course but is a excellent introduction for begin to study in this computer science field

par ANKIT S

5 juil. 2020

i would rather give 5 but as i wasted lot of time due to graphlab so i have take one star for that my satisfaction

par Sarra Z

22 janv. 2020

I liked this course, it is really based on study cases approaches and covers many problematics in machine learning

par Ankit T

29 août 2019

The course provided by Course era was really very good. I want to thank to Course era to give me this opportunity.

par Evan

28 juin 2021

Very nice teachers and good overall knowledge. However the discusion forum is dead and learning materials are old

par Bhaumik C

17 juil. 2020

Faculties were too good and explained very nicely. And I would recommend others this course for machine learning.

par golap h

2 juil. 2020

This machine learning course is really effective for beginners.I have learned many basic topics from this course.

par weiyuan x

12 avr. 2017

Good start course. It seems some information not covered so sometimes it is difficult to understand the content.