Chevron Left
返回到 Machine Learning: Regression

學生對 华盛顿大学 提供的 Machine Learning: Regression 的評價和反饋

4.8
5,471 個評分
1,016 條評論

課程概述

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....

熱門審閱

KM

2020年5月4日

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

2016年3月16日

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!

篩選依據:

326 - Machine Learning: Regression 的 350 個評論(共 983 個)

創建者 Yin X

2017年9月9日

Best course I have had so far on regression at Coursera. Thaaaaaank you Coursera and Washington U!

創建者 Milan C

2017年4月10日

Very nice course. The course gave me a good overview in how deep you can dive even with regression.

創建者 juan f r s

2016年5月15日

Excelent course and very well explained. Many thanks to both of you Emily and Carlos. All the best

創建者 Ramesh K

2016年3月6日

Lectures and assignments were awesome thanks to the professor for making this easier to understand.

創建者 Tahereh R

2019年4月2日

Thorough explanations of the essential concepts are provided! Valuable course and lectures.

Thanks!

創建者 Shalini S K

2016年4月18日

Great course! The course material was very well designed. Carlos and Emily are excellent teachers.

創建者 Nguyen T V

2016年1月17日

It's very interesting and challenging course, especially at the end. Thank you for your knowledge!

創建者 Matthew M

2016年1月5日

This course is an ideal mixture of theory, practical application, and coding. I really enjoyed it.

創建者 Rui W

2016年7月16日

Some practical skill and some theoretical knowledge are bought to me. I am so glad to enjoy them.

創建者 Stefano T

2016年2月10日

Very interesting course showing in a clear and easy to follow way the key concepts of Regression.

創建者 Omar B

2017年2月1日

Great course !

The best thing is when Emily talks about the intuition of each model or algorithm.

創建者 Rafael A

2016年2月22日

Once more, excellent delivery by Emily and Carlos. Looking forward to the classification course.

創建者 17 - 4 N B R

2020年6月25日

excellent course on regression. each and every concept is clear and in depth.Thank you Coursera

創建者 쥬

2016年5月24日

This course helped me a lot to understand regression. Now I can apply this idea to my own work.

創建者 Michaël L

2016年3月30日

Excellent course with lots of hands on !

The teacher is excellent and provide clear explanation.

創建者 Bokai C

2016年3月21日

Excellent Lectures!

Suggestions: homework results should be more representative and distinctive.

創建者 Med A D

2021年7月16日

Awesome course thank you so much for this valuable informations and good comprehinsive content

創建者 Chengye Z

2016年11月27日

It's a very helpful course. I really have leart a lot, by both watching video and programming.

創建者 uma m r m

2018年7月13日

The best course, I feel better and confident at regression concepts by the end of the course.

創建者 Jose P

2016年6月25日

Really good course. Professors are incredible. Very dynamic. The notes and videos are superb.

創建者 Aparajita K

2016年6月14日

All the mathematical details are very precisely and very well explained starting from basics.

創建者 Yinan W

2016年5月3日

A very good course. Glad all the assignments are also compatible with pandas and scikit-learn

創建者 Misha S

2016年2月28日

Exceptionally well organized, fun and full of useful content. Bravo to the course organizers!

創建者 Jorge S N

2016年2月22日

I liked very much the way this course is structured. Simple and complete. Very well done.

創建者 Wang L

2016年1月21日

An Excellent Course, that is able to provide insight and deep understanding about Regression.