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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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13,543 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

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：

1776 - Machine Learning Foundations: A Case Study Approach 的 1800 个评论（共 3,159 个）

创建者 Arif A

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May 18, 2016

Very practical course.

创建者 Daniele R

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Dec 14, 2015

molto bravi!

very good!

创建者 ANKIT G

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May 14, 2023

It was really nice ..

创建者 Anuj G

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Feb 6, 2023

A great course for ML

创建者 rebwar k

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Oct 8, 2020

it was amazing for me

创建者 Thientvse

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Jul 14, 2020

Very good, and detail

创建者 Amit L D

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Jun 21, 2020

It was a nice course.

创建者 Annanya J

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Jun 14, 2020

This course is fun :)

创建者 Akash G

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Mar 8, 2019

START basic like star

创建者 Tunuguntla S

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Mar 28, 2018

very nice interaction

创建者 JOSE R

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Nov 18, 2017

Awesome work. Thanks.

创建者 YangjiHYun

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Nov 14, 2017

Very GOOD!! Thank you

创建者 Vinoth H

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Jun 15, 2017

Very simple to learn.

创建者 Vijay K

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Apr 26, 2017

A wonderful course!!!

创建者 Mauro L

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Jan 19, 2017

Excellent Professors.

创建者 Brahmeswara Y

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Mar 27, 2016

Good overview course.

创建者 Kumar N

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Feb 14, 2016

Awesome for beginners

创建者 Amine L

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Oct 25, 2015

Great Course, thanks!

创建者 Robin P

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Jun 4, 2021

very pleasant course

创建者 KIRAN K

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Aug 27, 2020

excellent experience

创建者 ANMOL B 1

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Jun 3, 2020

Great way to explain

创建者 PARK J

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Oct 28, 2019

very easy to access,

创建者 Chandan K M

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Feb 26, 2019

well crafted course.

创建者 Brian N

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May 19, 2018

Its very refreshing.

创建者 Diego S L

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May 13, 2018

It's a great course!