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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：

1951 - Machine Learning Foundations: A Case Study Approach 的 1975 个评论（共 3,162 个）

创建者 Khushbu S

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Aug 6, 2020

It was Nice.

创建者 sathish v

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Jul 22, 2020

Wonderful ❣️

创建者 Sahil L

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Jul 12, 2020

Great Course

创建者 SPENCER P

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Jul 5, 2020

Great Course

创建者 Tarun B A

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Jul 2, 2020

Great Course

创建者 Manikant R

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Jun 17, 2020

Great course

创建者 JOYDIP M

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May 18, 2020

Very Helpful

创建者 Rodrigo P d S

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Jan 18, 2020

Excelente!!!

创建者 Muhammad Z H

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Aug 14, 2019

Learned alot

创建者 Germanno T

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Nov 20, 2017

Great course

创建者 Soumil D

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Nov 14, 2017

Loving this.

创建者 Dan S

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Dec 11, 2016

Great class!

创建者 sumita m

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Nov 5, 2016

great course

创建者 Ghassan F

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Oct 11, 2016

Great course

创建者 Luis D S

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Jun 4, 2016

Great Course

创建者 Clara C

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May 13, 2016

Great intro!

创建者 Chenxi W

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Mar 21, 2016

Really good.

创建者 Hans A

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Jan 31, 2016

Great course

创建者 Ravshan

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Jan 22, 2016

Good Course!

创建者 rajesh t

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Jan 13, 2016

Nice course!

创建者 Tianyuan L

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Dec 28, 2015

Great course

创建者 Josh M

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Dec 23, 2015

Great class!

创建者 Trevor S

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Dec 6, 2015

Great format

创建者 Liusicong

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Oct 12, 2015

Very useful!

创建者 Elamaran S

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Nov 11, 2024

good course