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学生对 华盛顿大学 提供的 Machine Learning: Regression 的评价和反馈

4.8
5,463 个评分
1,015 条评论

课程概述

Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets. Learning Outcomes: By the end of this course, you will be able to: -Describe the input and output of a regression model. -Compare and contrast bias and variance when modeling data. -Estimate model parameters using optimization algorithms. -Tune parameters with cross validation. -Analyze the performance of the model. -Describe the notion of sparsity and how LASSO leads to sparse solutions. -Deploy methods to select between models. -Exploit the model to form predictions. -Build a regression model to predict prices using a housing dataset. -Implement these techniques in Python....

热门审阅

KM

May 4, 2020

Excellent professor. Fundamentals and math are provided as well. Very good notebooks for the assignments...it’s just that turicreate library that caused some issues, however the course deserves a 5/5

PD

Mar 16, 2016

I really enjoyed all the concepts and implementations I did along this course....except during the Lasso module. I found this module harder than the others but very interesting as well. Great course!

筛选依据:

251 - Machine Learning: Regression 的 275 个评论(共 982 个)

创建者 Anirudh N

Jan 8, 2017

Very well organized course. After taking this course I am able to work on practical problems that can be solved using regression. Thanks Emily!

创建者 vishnu v

Jan 2, 2016

Great course on regression. Covers almost all aspects on how to build a regression model from scratch, also covers few advanced topics aswell.

创建者 Jane T

Jun 30, 2017

Difficult material, but the style of the lectures and assignments managed to keep it fun and interesting, all the way to the end. Amazing job

创建者 戴维

Mar 6, 2016

It is an excellent course, which can not only equip you with tools but also allow you to know the underlying reason. And it is interesting.

创建者 Leandro L R

May 12, 2018

This course is very good. It went above my expectations. The instructors are great and I learned a lot of Python here. I really recommend.

创建者 Nicolas P L

Jul 13, 2020

Great Course, it focused both in the theory and practical approaches in a challenging way such that you could learn better the concepts.

创建者 Yashaswi P

Sep 13, 2018

The only hindrance I had is with understanding the problem statements in assignments. It would be better to use a more unambiguous text.

创建者 Md F A

Nov 11, 2019

This is probably most in-depth Regression learning with python code, I have ever had. I liked the detail adventures of quizz questions.

创建者 Hemant V G

Mar 14, 2016

Course has covered regression in sufficient details and gave practical aspect of it. Thanks to Emily for very good content and teaching

创建者 Sathiraju E

Oct 31, 2018

It was great to take this course. Thanks to Carlos and Emily for their efforts. It's been a useful course and certainly worth my time.

创建者 Bharath K M

Jul 19, 2020

Very helpful in building good basics about regression and ML. Programming questions are very useful for practice and nicely prepared.

创建者 Harley J

Jul 18, 2017

Very solid course for understanding machine learning principles, including developing methodical approaches to solving data problems.

创建者 Joanna L

Mar 14, 2016

Excellent, step-by-step introduction to regression. The instructor takes her time to make sure every step is explained with details.

创建者 Xavi R

May 14, 2020

I loved this course. This is an excellent course for getting started in Machine Learning and I hope to complete the specialization.

创建者 Aayush A

Jul 12, 2018

This course is very good.I learnt a lot from it about regression.very recommended for all trying to get expert in machine learning.

创建者 Maria Z

Dec 27, 2017

Much more difficult than the first course. It would be challenfing for those who don't have programming skills and math background.

创建者 Michele P

Aug 23, 2017

Very nice explanation of ridge and lasso regression. Assignments are easier than in Classification. I highly recommend this course!

创建者 Ali A

Mar 5, 2016

All what I can say is if there is ten stars I would have given them to this course. It is just amazing and very very very helpful.

创建者 Pranas B

Mar 18, 2016

Amazing course with good balance of visual material, practice, and optional math. Thanks Emily and Carlos, you are great teachers!

创建者 Jacob M L

Mar 1, 2016

Well presented, practical, and hands-on. By far the best Data Science / Machine Learning series I have taken thus far on Coursera.

创建者 surendar r

Dec 23, 2018

In Depth coverage of lot of concepts, fully enjoyed it! Recommended to anyone wanting to explore in depth concepts of regression.

创建者 Abe E

Apr 28, 2017

Excellent. I used some of the videos to prepare and brush up for job interviews. Super helpful to play back at double speed ;-)

创建者 Wafic E

Nov 6, 2016

An amazing course. You can sense the effort put into the presentations and assignment work. Loving the specialization thus far.

创建者 Sergio D H

Feb 6, 2016

One of the best MOOCs I've ever tried. Great course materials and incredibly talented instructors. I can't recommend it enough.

创建者 Luciano S

Aug 7, 2017

I learned a lot of new concepts in this course. It is important to dive deeper than just understing how to use a set of tools.