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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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13,532 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

SZ

Dec 19, 2016

Great course! Emily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

筛选依据：

2801 - Machine Learning Foundations: A Case Study Approach 的 2825 个评论（共 3,157 个）

创建者 BIAN D

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Jun 15, 2016

homework could be more complicated

创建者 A d v

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Jan 9, 2022

i loved it excellent explanation

创建者 Royal P

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Nov 18, 2020

very knowlegdeful and interesting

创建者 Reginald A L

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Sep 20, 2020

A good course to learn. Thank You

创建者 Lee

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Oct 15, 2017

look this approach for beginners!

创建者 Yunqi H

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Jan 23, 2020

Great intro class but very fun !

创建者 Nitin K

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May 4, 2017

Pretty good introductory course.

创建者 Arish A

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Jun 7, 2016

A good introductory level course

创建者 Mario A G J

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Apr 25, 2016

Good for an introduction class.

创建者 Weiyi W

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Jun 11, 2018

Quizs are harder than lessons.

创建者 Mehul P

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Aug 1, 2017

Nicely explain use case of ML.

创建者 Jijo T

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Oct 6, 2015

I love the hands on exercises.

创建者 Mazen A G

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Oct 9, 2016

the best introduction for ML.

创建者 Rishabh C

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Jul 23, 2020

Awesome course to start with

创建者 Rakesh G

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Apr 15, 2019

A good beginners guide to ML

创建者 RISHAB P H

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Apr 15, 2020

add more practical's please

创建者 Mahesh B

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Oct 10, 2019

Good start for ML beginners

创建者 Poornima S

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Feb 18, 2019

It is designed really good.

创建者 Hyeong R J

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Feb 2, 2017

Good lecture and practices.

创建者 Marcos

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Aug 24, 2017

Great introductory course!

创建者 GABRIEL O C D O

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Apr 15, 2021

The course needs updating

创建者 SUPRIYA V S

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Jun 30, 2018

Nice course for beginners

创建者 Vinicius G d O

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Jun 23, 2016

Good introductory course.

创建者 José T G R

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Nov 1, 2015

Very good!!! Excellent!!!

创建者 Tushar A

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Jul 13, 2020

This is a nice course..