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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.

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：

2026 - Machine Learning Foundations: A Case Study Approach 的 2050 个评论（共 3,162 个）

创建者 Rogerio B

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May 14, 2016

Excellent!

创建者 Andrey B

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Apr 9, 2016

Thank you!

创建者 Pedro V H S

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Mar 5, 2016

I loved it

创建者 Veceslav K

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Dec 29, 2015

Super fun!

创建者 Andres F Z M

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Sep 26, 2024

Very good

创建者 Jorge L U V

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Oct 3, 2023

Excelente

创建者 Ritam G

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Apr 12, 2023

very good

创建者 Muhamad H

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Dec 30, 2022

very well

创建者 Christian J S

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Jul 22, 2022

excellent

创建者 Chaima E O

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Apr 12, 2022

excellent

创建者 Varuni N R

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Mar 23, 2022

Excellent

创建者 Charanya r Y

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Jan 30, 2022

excellent

创建者 ARBAZ A

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Jan 23, 2022

excellent

创建者 Vyshnavi G

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Jan 22, 2022

excellent

创建者 rasamsetty p

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Dec 14, 2021

excellent

创建者 PUPPALA L U

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Nov 27, 2021

excellent

创建者 Sri P N R L C S

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Nov 24, 2021

Thank you

创建者 KALYAN B

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Aug 12, 2021

Excellent

创建者 Kavish J

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Apr 18, 2021

excellent

创建者 Amilton V B

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Mar 12, 2021

Excellent

创建者 Shubham N

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Dec 12, 2020

Excellent

创建者 121910304062 g

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Nov 29, 2020

excellent

创建者 Pradeep S

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Nov 27, 2020

very nice

创建者 Shriram T

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Oct 15, 2020

very nice

创建者 Kratika H

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Sep 29, 2020

Excellent