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

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13,374 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

PM

Aug 18, 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.

SZ

Dec 19, 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.

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2026 - 2050 of 3,115 Reviews for Machine Learning Foundations: A Case Study Approach

By Pradeep S

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Nov 28, 2020

very nice

By Shriram T

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Oct 15, 2020

very nice

By Kratika H

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Sep 29, 2020

Excellent

By Nachiket R K

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Sep 25, 2020

EXCELLENT

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Sep 22, 2020

Excellent

By Rahul D

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Sep 21, 2020

wonderful

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Sep 21, 2020

Excellent

By miguel s

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Sep 20, 2020

very well

By Vaibhav K

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Sep 19, 2020

excelient

By Karim H

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Sep 18, 2020

excellent

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Sep 16, 2020

excellent

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Sep 15, 2020

Excellent

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Sep 13, 2020

Excellent

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Sep 9, 2020

Excellent

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Sep 6, 2020

Excellent

By Neha K

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Sep 1, 2020

EXCELLENT

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Aug 31, 2020

excellent

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Aug 17, 2020

very good

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Aug 15, 2020

EXCELLENT

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Aug 15, 2020

EXCELLENT

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Aug 5, 2020

Excellent

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Aug 4, 2020

excellent

By Bhanu P S

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Jul 29, 2020

excellent

By DEEP K S

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Jul 26, 2020

very good

By Majd A

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Jul 23, 2020

thank you