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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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13,550 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

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.

RH

Jun 8, 2017

I felt this course did a good job introducing the student to Machine Learning. The examples and hands on assignments brought the concepts home. I was able to use the knowledge immediately at work.

筛选依据：

2101 - Machine Learning Foundations: A Case Study Approach 的 2125 个评论（共 3,162 个）

创建者 于飞飞

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May 14, 2016

very good

创建者 Xinwei L

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May 2, 2016

very cool

创建者 Pradeep M

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Apr 4, 2016

Excellent

创建者 Maxwell N M

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Dec 12, 2015

Very Cool

创建者 Giovanni C A

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Nov 2, 2015

Excellent

创建者 Zhenis A

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Oct 22, 2024

Огонь!!!

创建者 Gaurav P

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Apr 26, 2023

3700Rs/-

创建者 Ayoub I

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May 17, 2022

good job

创建者 Mustefa A U

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Dec 19, 2020

good job

创建者 Malèk R

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Oct 11, 2020

Good job

创建者 mahantesh k

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Sep 24, 2020

excelent

创建者 S. M S H

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Sep 4, 2020

Good one

创建者 Md. T U B

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Jul 10, 2020

excelent

创建者 GIRISH S

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Jun 27, 2020

nice one

创建者 Steve F S

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Apr 27, 2020

awesome!

创建者 mengheng x

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Jun 11, 2018

h很不错的入门课

创建者 Shikha A

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May 6, 2018

Awesome!

创建者 Aaryesh K

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Apr 4, 2018

too good

创建者 张业伟

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Sep 17, 2017

Perfect!

创建者 Allen P

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May 19, 2017

awesome!

创建者 任晨熙

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Jan 28, 2017

很专业，正在学习

创建者 Chaney C

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Nov 6, 2016

入门级别收获良多

创建者 Việt N T H

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Aug 6, 2016

Awesome!

创建者 Erickson M

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Jun 18, 2016

Excelent

创建者 Haider A

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Apr 9, 2025

amzaing