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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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1751 - Machine Learning Foundations: A Case Study Approach 的 1775 个评论（共 3,162 个）

创建者 shubham k

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Apr 8, 2019

this was really learning

创建者 Sanjiban B

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Nov 27, 2018

Great course. Thank you.

创建者 ILYAS C

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May 29, 2017

Clear and easy to follow

创建者 Alireza R

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May 29, 2017

The best instructor ever

创建者 Rodolfo S

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May 8, 2016

Great course! Thank you.

创建者 Tayson H

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Mar 4, 2016

觉得dato很好用，加上老师讲得非常好，good

创建者 Yang G

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Nov 29, 2015

good, have learned a lot

创建者 SHARMISTHA G

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May 4, 2023

good informative

course

创建者 Gaurav K

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Sep 10, 2020

very good course to do.

创建者 programing k

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Jul 20, 2020

bATTER WAY FOR BEGINEER

创建者 Dr. N P M

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May 26, 2020

Very informative course

创建者 Danish H K

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Sep 5, 2017

Awesome Learning course

创建者 ASHISH D

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May 28, 2017

A must for ML aspirants

创建者 Haoyu J

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Apr 25, 2017

Good introduction to ML

创建者 Túlio C

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Jan 23, 2017

Enthusiastic professor.

创建者 YongKwan K

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Jan 11, 2016

This couser is awesome.

创建者 Saeed U R

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Oct 4, 2020

Remarkable experience.

创建者 Mrs.M.Amal M C T

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Sep 10, 2020

GOOD COURSE,GOOD CLASS

创建者 KARTHICK G

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Aug 30, 2020

It's a best I think so

创建者 Prabhakar A

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Aug 15, 2020

A wonderful experience

创建者 Kedar P

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May 3, 2020

good foundation course

创建者 ANKUR S

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Mar 20, 2020

best one for beginners

创建者 Afaque A

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Aug 20, 2017

Excellent Explanation.

创建者 Shivam A

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May 10, 2017

Amazing for beginners.

创建者 Chandima

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Dec 26, 2016

Brilliant introduction