Machine Learning: Regression(으)로 돌아가기

# 워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
4,548개의 평가
850개의 리뷰

## 강좌 소개

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....

## 최상위 리뷰

##### PD

Mar 17, 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!

##### CM

Jan 27, 2016

I really like the top-down approach of this specialization. The iPython code assignments are very well structured. They are presented in a step-by-step manner while still being challenging and fun!

필터링 기준:

## Machine Learning: Regression의 821개 리뷰 중 301~325

교육 기관: Rafael A

Feb 23, 2016

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

교육 기관: Jooho S

May 24, 2016

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

교육 기관: Michael L

Mar 30, 2016

Excellent course with lots of hands on !

The teacher is excellent and provide clear explanation.

교육 기관: Bokai C

Mar 22, 2016

Excellent Lectures!

Suggestions: homework results should be more representative and distinctive.

교육 기관: Chengye Z

Nov 28, 2016

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

교육 기관: mahesh

Jul 13, 2018

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

교육 기관: Jose P

Jun 25, 2016

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

교육 기관: Aparajita K

Jun 14, 2016

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

교육 기관: Yinan W

May 03, 2016

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

교육 기관: Misha S

Feb 29, 2016

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

교육 기관: Jorge S N

Feb 22, 2016

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

교육 기관: Wang L

Jan 21, 2016

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

교육 기관: Popovics L

Dec 29, 2015

Harder than the previous course, but helps to understand machine learning regression in deep.

교육 기관: Deleted A

Nov 21, 2016

Excellent course. Concepts are explained clearly and the exercises reinforce understanding.

교육 기관: Arash A

Oct 26, 2016

Practical course complete with great content, assignment, and everything else that you need.

교육 기관: Saurabh S

Oct 21, 2016

Course made me understand elastic net(lasso+ridge) which helped me in my modelling project

교육 기관: Med N

Jan 11, 2016

One of the best courses I have taken!

Very good balance of depth and breadth of the material.

교육 기관: Thomas E

May 12, 2016

A bit to easy to get through the exercises but otherwise very enlightening and inspirering.

교육 기관: Guomao X

Sep 20, 2016

the material is solid and using python is a good way to learn machine learning programming

교육 기관: Steven R

Aug 15, 2016

Great introduction to Regression, would recommend to anyone looking to make a start in ML.

교육 기관: Ingrid B

Aug 12, 2016

Really excellent guided course. Well explained and very useful exercises. Highly recommend

교육 기관: Marnix W

Mar 22, 2016

Great course well taught. Amazed about the in depth course material and practices. Thanks!

교육 기관: Peter G

Feb 26, 2016

Excellent presentation of fundamental concepts and good overview of some specific methods.

교육 기관: Jhonatan J

Feb 01, 2016

great course, I learned a lot. Videos, slides, quiz, programming exercises, a lot of fun.

교육 기관: Suoyuan S

Jan 21, 2016

Good course, but could improve the quiz. Currently the quiz are too easy for ML learners.