Chevron Left
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
星
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

SS

May 18, 2020

The course was very informative but I face a lot of problems in installing Graphlab and Turicreate. I request the Mentors please use the Pandas data frame in place of SFrame. The mentors are cool.

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：

1001 - Machine Learning Foundations: A Case Study Approach 的 1025 个评论（共 3,159 个）

创建者 Subramanyam R

•

Apr 25, 2020

This course is very interesting and i hope so many topics are covered in machine learning

创建者 Syed T S

•

Apr 18, 2020

A very unique course which totally focuses on practical applications of machine learning.

创建者 David R R

•

Jul 10, 2017

I think it is a quite interesting and helpful introduction to the rest of the ML modules!

创建者 KUMAR K

•

Oct 30, 2016

A wonderful foundation course on Machine Learning to understand its various facets... !!!

创建者 Dariusz B

•

Feb 7, 2016

I liked it a lot. 1 remark: Some questions in quizzes were not clear 100% in my opinion.

创建者 Lesly

•

Jan 14, 2016

Superb course - Anyone can easily learn. Case study approach is the right way to learn ML

创建者 Meghana S

•

Dec 13, 2023

The videos explaining the concepts were crystal clear. The assignments were interesting.

创建者 Noor A K

•

Jun 26, 2020

Sorry I didn't knew that prior knowledge is required. so i started learning python first

创建者 邵典

•

Mar 23, 2020

teachers are very good. cases are interesting! i learn a lot from the course, Recommend!

创建者 Yuhuan Z

•

Jan 30, 2020

Very good introduction to machine learning theory. The content is also very interesting.

创建者 Dohyoung C

•

Apr 30, 2019

Great course !!!

I really enjoyed it.

I hope to deep dive into details in next courses...

创建者 Yinping Z

•

Aug 20, 2017

Very impressive. Teachers created a simple way to help us understand complicated things.

创建者 Qing-Qi C

•

Oct 4, 2016

Clearly course, but still hope to get more information about how to use other frame work

创建者 Pawan S

•

May 17, 2016

best teaching approach .

i think this approach should be adapted for other courses also

创建者 SUBHAM M

•

Apr 27, 2016

Awesome course. But i suggest more flexibility in deadline of submission of assignments.

创建者 Azad K T

•

Nov 1, 2015

An extremely helpful course for beginners. I wish to do all of it's proceeding courses..

创建者 Sina G

•

Mar 19, 2021

Best Machine Learning Course on Coursera! and for Free. Thank you for the awesome work!

创建者 Val V

•

Oct 29, 2020

Very nice intro to machine learning. Looking forward to the next courses in the series.

创建者 Vishalini

•

May 20, 2020

The very idea of case study approach is awesome and thus concept clarity is the maximum

创建者 Sandra L

•

Aug 20, 2017

I have learned the basics about Machine Learning in a simple way :) Highly recommended.

创建者 Ida C

•

Jun 5, 2017

This course is interesting, it is good for someone know nothing about machine learning.

创建者 Chris M

•

Feb 28, 2017

This course did an excellent job of introducing the basic concepts of machine learning.

创建者 Dj S

•

Oct 26, 2016

This 1st course was excellent, others in the specialization moved quicker than expected

创建者 Nilesh K

•

Jul 9, 2016

beautiful overview of ml tools available. kudos to carlos and emily, thank you so much!

创建者 Sharad J

•

Mar 23, 2019

The ML concept is explained with use cases and demonstrated with python programs which