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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

4.6
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

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.

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:

1701 - Machine Learning Foundations: A Case Study Approach 的 1725 个评论(共 3,159 个)

创建者 Andres F R V

Nov 17, 2020

very good,,,, i am happy. i

创建者 Anji B P

Jun 6, 2019

Good Course with case study

创建者 Chen G

Feb 27, 2017

A great introductory to ML.

创建者 Awantik D

Feb 9, 2017

Perfect for getting started

创建者 Sam C

Oct 23, 2016

interesting to follow alone

创建者 Oleksii R

Jun 4, 2016

Great course. Thanks a lot.

创建者 Vijai K S

Dec 5, 2015

So far it has been awesome.

创建者 Mustapha B

Jul 19, 2022

Excellent !! thank you !!

创建者 Merve E U

Dec 13, 2020

Thank you for your support

创建者 Ben R

Oct 17, 2020

great course very useful!!

创建者 T P R

Aug 14, 2020

its best to learn this way

创建者 Tianshu W

Jul 28, 2020

Loved it! I learned a lot!

创建者 Sinmileoluwa T

Jun 23, 2020

This course was excellent!

创建者 Christy C R

Jun 5, 2020

Great course for beginners

创建者 Shreyansh P

Oct 6, 2018

it was very helpful course

创建者 Roxana N V

Mar 25, 2017

Great introductory Course.

创建者 Ahtasham H

Feb 5, 2017

Amazing Learning approach.

创建者 Socrates M

Nov 20, 2016

It is really cool course .

创建者 Rabish K

Oct 21, 2016

Excellent. Very Intuitive.

创建者 Danish R

Oct 14, 2016

A good introductory course

创建者 Ehsan T

Oct 11, 2016

the best Course i ever see

创建者 Vikash M

Sep 13, 2016

Great course for starters!

创建者 felix a f a

Feb 21, 2016

Really Good Introduction!!

创建者 Soumya R

Feb 4, 2016

Great for beginners in ML!

创建者 Deleted A

Jan 6, 2016

Great intro to the ML area