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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!

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1851 - Machine Learning Foundations: A Case Study Approach 的 1875 个评论（共 3,162 个）

创建者 Israel C

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May 22, 2017

Excellent Course!

创建者 Ji H

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Jan 11, 2017

excellent course.

创建者 Dheeraj A

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Jan 2, 2017

Excellent Course.

创建者 Shan-Jyun W

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Dec 31, 2016

Excellent course!

创建者 gaozhipeng

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Dec 26, 2016

NICE INTRODUCTION

创建者 Saksham S

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Oct 8, 2016

Very good course.

创建者 Mario A R M

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Sep 16, 2016

Excellent course!

创建者 Liang Q

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Sep 12, 2016

good intro course

创建者 Vincent L

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Aug 18, 2016

Excellent Course!

创建者 Apurva A

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Mar 2, 2016

Excellent Course!

创建者 Anthony

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Nov 1, 2015

fantastic teacher

创建者 Nar N

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Oct 30, 2024

Very Good Course

创建者 Sunil k

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Jul 22, 2022

very good course

创建者 Amlan D

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May 4, 2022

Excellent Course

创建者 SUDABATHULA J P

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Dec 5, 2021

excellent course

创建者 Melisha Q

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Jul 4, 2021

very good course

创建者 Kalpana j

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May 6, 2021

excellent course

创建者 Jubair A

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Apr 6, 2021

Very nice course

创建者 Thangaraju, S

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Mar 7, 2021

Excellent course

创建者 SUGUNA M

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Nov 18, 2020

excellent course

创建者 ANUJ S

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Sep 28, 2020

Excellent Course

创建者 VIGNESH K

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Sep 4, 2020

Send certificate

创建者 Kumar S

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Sep 1, 2020

great experience

创建者 Rushi B

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Jul 24, 2020

excellent course

创建者 DHARMESHWARAN S

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Jul 13, 2020

excellent course