Chevron Left
Retour à Machine Learning Foundations: A Case Study Approach

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

4.6
étoiles
13,206 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

SZ

19 déc. 2016

Great course!

Emily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

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

Filtrer par :

2676 - 2700 sur 3,065 Avis pour Machine Learning Foundations: A Case Study Approach

par Dai W

3 janv. 2016

I cannot review my completed homework. It's very boring.

par Lena M

22 déc. 2015

Loved the course, the teachers, the case study approach.

par DARSHI A

12 juil. 2020

It is a good course and proffesors are explaining cool.

par Andrew G L

4 août 2017

Good introduction. Don't expect more than that though.

par Wangjun

29 déc. 2016

This course is very good.Thankyou for all the teachers.

par SUHARIKA V

26 nov. 2021

the experiance is good and assignments are interesting

par TAMATAM V S P R

11 août 2020

The course about machine learning is awesome.

thank you

par Alain C

15 févr. 2019

Technical setup is not easy, but great business cases.

par Mykhaylo K

30 oct. 2020

More practical approach and nothing theoretical (yet)

par SATYA P A

29 avr. 2020

its was very useful to learn about machine learning !

par rajeev r

1 oct. 2019

wonderful experience. It's like doing a live project.

par Abdulrahman M A K

10 juil. 2019

Awesome instructors and great knowledge and practices

par Divya v M

28 mai 2016

Great overview and broad foundation of all techniques

par Jorge S N

9 avr. 2016

El más intuitivo curso de ML que he visto en Coursera

par HARSHIT J

7 juin 2020

Average Course, don't have much expectations from it

par Bhakthavatsala R

16 juin 2018

Interactive and very interesting. good for beginners

par Fenjin W

15 avr. 2016

Great course! Hope the slides gets better annotated.

par Prashant D

16 juin 2020

The course was awesome and so does the Instructors!

par Yagyansh S K

2 déc. 2016

Awesome Teaching Technique Used! Kudos To The Team!

par Swechchha A

17 déc. 2022

i wished they taught using pandas scikit-learn too

par Mitali C

10 juin 2020

It was Amazing course ,with amazing instructors :)

par Avinash P M

13 déc. 2016

Assignments could have been little more difficult.

par Alvin B K

17 août 2020

Carlos and Emily are really cool. They're cool 😀

par 吴青

6 déc. 2017

didn't reach my expectation but still quite good.

par Albert Z

6 févr. 2016

Hands on should have been more involved/dificult.