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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:

1726 - Machine Learning Foundations: A Case Study Approach 的 1750 个评论(共 3,159 个)

创建者 Fangyi Z

Nov 19, 2015

This course is good for me

创建者 Tommy W

Oct 19, 2015

Very good!!! Super helpful

创建者 이원일

Feb 21, 2022

머신러닝의 핵심적인 부분을 학습할 수 있었다.

创建者 Yash J

Jul 27, 2020

Excellent Teaching Method

创建者 Salman T

Jul 23, 2020

Thank you for teaching us

创建者 Vishal K

Feb 23, 2020

Very much hands on course

创建者 Lan J

Nov 1, 2018

Love it. Easy and useful.

创建者 Saifullah

Jun 7, 2018

Very well designed course

创建者 Naga V

Mar 30, 2018

great course for starters

创建者 PengChienKai

Aug 3, 2017

Very nice for learning ML

创建者 Jiaqi Z

Sep 25, 2016

very clear and practical!

创建者 Omar A C T

Aug 29, 2016

it was a exciting course

创建者 Amit K

May 23, 2016

Awesome course structure.

创建者 Sean L

May 21, 2016

very good course about ML

创建者 Mohammad

Feb 15, 2016

Really Good for beginners

创建者 Amit T

Jan 30, 2016

Excellent overview of ML!

创建者 Pandu R

Jan 6, 2016

Great intro course in ML.

创建者 Alejandro G L

Nov 30, 2015

Great introductory course

创建者 Mykhailo K

Oct 7, 2021

Cool introduction to ML!

创建者 Yoko S

May 14, 2021

Long course and valuable

创建者 RAVINDRA K S

Sep 18, 2020

Nice course for learning

创建者 akhila g

Apr 12, 2020

very useful online class

创建者 Umirbek M

Oct 9, 2019

Very interesting course.

创建者 JAMES R P B

Sep 13, 2019

Great studying materials

创建者 shubham k

Apr 8, 2019

this was really learning