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Learner Reviews & Feedback for Machine Learning Foundations: A Case Study Approach by University of Washington

4.6
stars
13,550 ratings

About the Course

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....

Top reviews

DS

Sep 28, 2015

Excellent course, with really good lectures, material and assignment. Plus the professors are really amazing and their enthusiasm is really refreshing and makes the class more interesting. Loved it!

BL

Oct 17, 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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3151 - 3162 of 3,162 Reviews for Machine Learning Foundations: A Case Study Approach

By Nguyen K D

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Jun 18, 2020

Coursera Scam Auto Subcription. Free Fuckers

By Jeni

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Apr 17, 2020

Instructional videos were unclear.

By Ali A

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May 15, 2024

Require usage of outdated library

By MD D I

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Jun 26, 2020

I want to un enroll this course

By abhishek s

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Jun 18, 2020

Not a good course to study

By James P

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Sep 15, 2023

Can't do it on M1 chip

By Wenjun X

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Jul 23, 2022

Poor version support

By Jorge L G A

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Sep 24, 2020

no esta en español

By fuzhi z

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Dec 9, 2020

Not recommend

By Jijo J

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Apr 25, 2021

Outdated

By Bhavya C

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Mar 18, 2021

worst

By ABOORVA M S

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May 24, 2020

worst