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

13,084 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


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.


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

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3026 - 3043 sur 3,043 Avis pour Machine Learning Foundations: A Case Study Approach

par Arpit S

22 mai 2020

Improve the quality of quizes. Need to focus more on algorithm part.

par Pratick B

8 août 2021

I​nstallation of Sforce and turi was not shown adequately enough.

par Mohamed M

28 sept. 2021

import turicreate is hard to install and class based on it

par Eunyoung C

29 août 2020

This course could be better to use general python library.

par Christian C

5 juin 2021

El curso es bueno pero esta completamente desactualizado

par Sunita b l

4 juil. 2020

Provide the good notes and video so all concept clear.

par Melissa F

2 août 2021

cannot get the tools installed to do any of the work.

par Nguyen K D

18 juin 2020

Coursera Scam Auto Subcription. Free Fuckers

par Gencho Z

3 juil. 2022

Wors ML course I've had on Coursera so far.

par Jeni

17 avr. 2020

Instructional videos were unclear.

par MD D I

26 juin 2020

I want to un enroll this course


18 juin 2020

Not a good course to study

par jazz p

23 juil. 2022

Poor version support

par Jorge L G A

23 sept. 2020

no esta en español

par fuzhi z

8 déc. 2020

Not recommend

par Jijo J

25 avr. 2021


par Bhavya C

18 mars 2021



24 mai 2020