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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

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

MK

Jul 20, 2019

A great course, really designed to understand the underlying core concepts of machine learning using real-life examples which takes you through all that with little to no programming skills required!

筛选依据：

2001 - Machine Learning Foundations: A Case Study Approach 的 2025 个评论（共 3,162 个）

创建者 Tony G

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Sep 17, 2017

Really cool

创建者 태경 이

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Sep 14, 2017

very good !

创建者 王曾

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Sep 9, 2017

good course

创建者 Weilin C

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Aug 26, 2017

very detail

创建者 Néstor R E P

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Feb 8, 2016

Outstanding

创建者 Chengjun J

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Feb 8, 2016

good start!

创建者 Thuong D H

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Jan 13, 2016

Good course

创建者 Zhalgas N (

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Nov 5, 2024

Все хорошо

创建者 Vaibhav K

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Sep 19, 2022

Excellent

创建者 Riya G

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Jul 13, 2022

good couse

创建者 蔡孟蓁

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Mar 31, 2021

有難度但可以學到很多

创建者 ROBAD M

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Nov 26, 2020

excellence

创建者 Bhavesh J

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Nov 14, 2020

Fantastic!

创建者 Durodola A D

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Aug 31, 2020

excellent!

创建者 Rohit R D

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Aug 15, 2020

Regression

创建者 LUIS A M Y

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Jul 25, 2020

Excelent!!

创建者 Ifzal A M

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May 19, 2020

excellent.

创建者 Anunathan G S

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Aug 5, 2018

Lucid over

创建者 Nancy L

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Apr 27, 2018

Thank you!

创建者 carloswhite

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Mar 17, 2018

it is nice

创建者 zulfikar A

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Dec 30, 2017

Best .....

创建者 康佳星

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Sep 13, 2017

入门基础的成就感不错

创建者 王泽元

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May 13, 2017

meaningful

创建者 Júlio T

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Mar 24, 2017

Very Good!

创建者 Frank

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Oct 31, 2016

实践与理论的完美结合