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返回到 Machine Learning Foundations: A Case Study Approach

学生对 University of Washington 提供的 Machine Learning Foundations: A Case Study Approach 的评价和反馈

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13,551 个评分

课程概述

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....

热门审阅

AH

Mar 27, 2022

very nice course.If you have basic knowledge of python datastructure then this course is best to start data science.All contents are beginner friendly which makes this course easily understandable.

RM

Feb 2, 2022

I was very disappointed with the exclusion of the final courses and the capstone project. The most interesting part of specialization no longer exists and no plausible justification has been given.

筛选依据：

1926 - Machine Learning Foundations: A Case Study Approach 的 1950 个评论（共 3,162 个）

创建者 Viet N

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Nov 25, 2015

Awesome course

创建者 kardoworld

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Oct 28, 2015

Awesome Course

创建者 Carlos A P

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Oct 15, 2015

Really great !

创建者 ARYAN G

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May 21, 2023

decent enough

创建者 vamsi k k

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Jan 27, 2022

great vision!

创建者 Hendro U

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Sep 27, 2020

HENDRO MANTAP

创建者 KONETI S

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Jun 18, 2020

its very good

创建者 Dr. R R N

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May 11, 2020

Great classes

创建者 Rahul R

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Apr 23, 2020

More pratical

创建者 Bala

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Jun 6, 2019

Nice Teachers

创建者 Xue

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Dec 2, 2018

Great course!

创建者 WEI Y

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Jul 5, 2018

Great course!

创建者 PiKaChu

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Nov 26, 2017

good learning

创建者 hari p b

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Sep 18, 2017

Great course.

创建者 Vitalie D

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Jun 27, 2017

Great course!

创建者 오재욱

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Jan 16, 2017

great it was

创建者 Runzhe C

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Jan 2, 2017

Great Course!

创建者 Nicholas S

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Oct 7, 2016

Great course.

创建者 Anaís G

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Apr 22, 2016

great course!

创建者 NAMAN J

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Apr 20, 2016

Good Content!

创建者 Mohammad H

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Jan 20, 2016

great course!

创建者 Purushoth R

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Oct 3, 2015

Great course.

创建者 Бек М

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Oct 30, 2024

Очень хорошо

创建者 DOSHI, U

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Jul 13, 2023

Great Course

创建者 Sankhadip J

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Aug 30, 2020

Good subject