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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

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.

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.

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1801 - Machine Learning Foundations: A Case Study Approach 的 1825 个评论（共 3,162 个）

创建者 Diego S L

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May 13, 2018

It's a great course!

创建者 stephon_lu

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Nov 8, 2017

the course is great!

创建者 Sarah N

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Apr 23, 2017

Great Intro into ML.

创建者 Yongrui H

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Mar 14, 2017

This course is good.

创建者 Irina L

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Jan 29, 2017

Vary good course!!!!

创建者 Sumit S

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Sep 3, 2016

Best hands on course

创建者 Lucas T

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Dec 6, 2015

Really great course!

创建者 Vahid R

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Apr 12, 2022

I realy enjoyed it.

创建者 Sankul P

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Sep 14, 2021

excellent thank you

创建者 Antonios M

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Feb 10, 2021

It's a great course

创建者 Raj K

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Dec 15, 2020

Very knowledgeable.

创建者 Neeti M

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Oct 31, 2020

good.. i like it...

创建者 TEJAL H

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Jul 30, 2020

Fabulous instructor

创建者 MALLAIAH V

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Jun 12, 2020

it is very helpfull

创建者 Dimaz A P

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May 23, 2020

Best course so far!

创建者 Magdi M

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Sep 10, 2018

Great case coverage

创建者 nayan m

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Apr 5, 2018

Challenging and fun

创建者 Yue

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Feb 24, 2018

Really great course

创建者 Trinh N Q

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Jan 11, 2018

Great course so far

创建者 Preetham G

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Nov 1, 2017

I loved this course

创建者 Djibril N

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Jan 4, 2017

Complete and great.

创建者 Georgios

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Oct 3, 2016

Absolutely amazing.

创建者 Roger S

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Sep 3, 2016

This course is COOL

创建者 ADESH T B M 2 B

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Apr 18, 2021

THANK YOU COURSERA

创建者 Luis T

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Mar 25, 2021

Lovely experience.