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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.

筛选依据：

1826 - Machine Learning Foundations: A Case Study Approach 的 1850 个评论（共 3,162 个）

创建者 Shuchih N

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Nov 4, 2020

QUITE good

😊😊😊😊

创建者 rs

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Oct 21, 2020

Usefull to learing

创建者 JAKKA S P S

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Oct 5, 2020

Its perfect course

创建者 Sarthak S

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Aug 23, 2020

very nice and easy

创建者 Diego L

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Aug 5, 2020

Excelente Curso!!!

创建者 Harshita K

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Jul 14, 2020

Good for beginners

创建者 Moe K O

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Jun 28, 2020

I love this course

创建者 Nagarajapandian

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Jun 16, 2020

Very useful course

创建者 IDOWU H A

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May 20, 2018

These Traininers a

创建者 Jing

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Aug 14, 2017

Good for beginners

创建者 Muhammad U

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Aug 11, 2017

Excellent Teaching

创建者 Nancy Q

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Feb 13, 2017

highly recommended

创建者 Adrian B

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Sep 14, 2016

Very recommendable

创建者 Chen Y

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Feb 18, 2016

It's a neat course

创建者 Vlad G

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Jan 29, 2016

amazing experience

创建者 DEVINENI T

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Oct 6, 2022

its very helpful

创建者 Fevzi E K

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Oct 11, 2020

gerçekten çok iyi

创建者 SHARUKH A

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Jul 18, 2020

great course.....

创建者 Bhavya D J

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Jun 15, 2020

amazing course...

创建者 Abhay S

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Jun 14, 2020

i love course era

创建者 Ridwanul H T

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Apr 11, 2020

Excellent course.

创建者 Shiwanshu K

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May 19, 2019

Beautiful course!

创建者 Yaakov M

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Jun 16, 2017

Nice introduction

创建者 Bum-Joo C

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Jun 2, 2017

Good! and Useful!