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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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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

BL

Oct 16, 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

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.

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2226 - Machine Learning Foundations: A Case Study Approach 的 2250 个评论（共 3,159 个）

创建者 Wu C

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Jul 1, 2018

good

创建者 Xuewei C

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Jan 7, 2018

帮助很大

创建者 JoonHyun J

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Nov 26, 2017

good

创建者 HuaTao L

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Jul 30, 2017

good

创建者 Joydip G

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Jun 1, 2017

good

创建者 dilu583

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Apr 12, 2017

good

创建者 Yu-Jhen-Wu

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Jan 9, 2017

Nice

创建者 Emeka J

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Jan 5, 2016

good

创建者 Esteban A

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Sep 25, 2015

FUN!

创建者 SAI V K

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Aug 27, 2020

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创建者 Vansh S

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May 10, 2019

nic

创建者 TMU b

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Jul 18, 2023

NC

创建者 Stephen G

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Jan 15, 2021

NA

创建者 LIPSA R B

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Sep 11, 2020

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创建者 Douba J

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May 28, 2020

bn

创建者 A R R

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Apr 27, 2020

ok

创建者 Magdiel A

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May 6, 2019

Ok

创建者 SongMyungjin

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Oct 12, 2017

ok

创建者 Younghwan K

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Dec 24, 2016

Ex

创建者 Alexander A S G

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Dec 25, 2015

ok

创建者 Naman G

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Jul 17, 2025

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创建者 JINO R

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Nov 27, 2020

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创建者 PARMAR M

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Oct 22, 2020

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创建者 kyasa P

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Jul 11, 2020

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创建者 Sanjeev k

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Jan 24, 2019

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