Machine Learning: Regression(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
별점
5,354개의 평가
999개의 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

KM
2020년 5월 4일

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
2016년 3월 16일

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!

필터링 기준:

Machine Learning: Regression의 966개 리뷰 중 201~225

교육 기관: Liang-Yao W

2017년 6월 26일

I like the step-by-step introduction that familiarize one with the important concepts. I also like the nice explanation and visualization of some relevant mathematics. Recommended.

교육 기관: Oshan

2017년 6월 22일

thorough explanation. they cover most of the topics. lessons on ridge and lasso regression are great. would recommend for anyone looking to get into data science/ machine learning.

교육 기관: Holger P

2016년 9월 30일

Great course covering Regression Machine Learning. Gives a great introduction to this topic. Teaching the methods using a case study yields for great illustrations of the concepts.

교육 기관: Andrea C

2016년 8월 16일

This course is damn well structured. Course material is great and programming assignments are interesting and helps you to really understand how to implement regression algorithms.

교육 기관: George K

2016년 3월 9일

The professors help understand the concepts from ground up. Seriously recommended course if you want to know how Regression works and all about ridge, lasso and kernel regression.

교육 기관: Yabin W

2019년 8월 4일

The course goes into great details to clarify difficult concepts. Besides, the assignments are well designed so that students can grasp the topic step by step through practicing.

교육 기관: Lennart B

2016년 2월 7일

Thorough introduction to regression, the assignments are demanding, and the teachers very engaging. It would be nice if a wider range of applications and examples were presented.

교육 기관: Joseph F

2018년 3월 19일

Very good course with nice slides and clear interpret, and the assignment with ipython is really well designed because it already give you the illustration of each step. Thanks!

교육 기관: Ed S

2018년 3월 2일

You will get a good grasp of Linear Regression, Ridge Regression, Lasso and potential use for feature selection, gradient descent, coordinate descent, numpy and graphlab create

교육 기관: Salim L

2017년 8월 27일

Goes well beyond the statistics that I learned in engineering! Key concepts in regression such Ridge, Lasso and KNN. Use Python to build all your algorithms from the ground up.

교육 기관: Omar N T

2016년 3월 30일

it gave more details than my class room. it also adopts a practical approach to learn. it is a great course in regression especially for practitioners.

Thanks Carlos and Emily :)

교육 기관: Dipankar N

2017년 12월 11일

Great course on Regression. This will help build basic for upcoming modules. Emily teaches the concepts in a simple way. I liked the structure and coverage of Regression topic.

2017년 5월 6일

Great material, this was tougher than the previous course. It is challenging and more exercises to practice which help to a better understanding of the concepts. Great mentors!

교육 기관: Rahul J

2017년 4월 2일

An extremely well designed course, I am an instructional designer myself, so adding weight to the words. Would have appreciated a few more assignments for the last week though.

교육 기관: Chengcheng L

2015년 12월 27일

I feel I understand regression models better than before. But I still need to read more books on the same topic to actually convert what I learned here to long term memory :)

교육 기관: Lavaneesh S

2019년 9월 17일

Fantastic Course, allowed me to gain insights to regression. Both the instructors like always have been excellent. Shout out to coursera for allowing me to take this course!

교육 기관: 陈哲鸿

2018년 5월 19일

It's a really nice course.What i've learned in this course: how to implement a regression model through my own hands, assessing performance, feature selection...and so on.

교육 기관: clara c

2016년 5월 13일

This course is very well organized and all the information is relevant. Everything is explained in great detail. The exercises really make you feel that you are learning.

교육 기관: Do H L

2016년 1월 13일

All the courses in this specializations are very well-made and rigorous. I think all MOOCs, especially techinical ones, should be as well-designed as this or even more.

교육 기관: Fahim K

2016년 1월 6일

The course is really helpful. It has started with simple Regression model and gradually build the different advance regression model. Thanks for this wonderful course.

2016년 8월 15일

rigorously explained some of the most important algorithms in regression world, also the pros and cons of using certain algorithm for certain conditions. totally worth

교육 기관: Sahil D

2016년 5월 15일

Good overall theoretical and practical explanation of the material, I was also able to use scikit learn and pandas without any difficulties instead of graphlab create.

교육 기관: isanco

2016년 1월 25일

Great class (really liked the graphical interpretations of Lasso and Ridge optimizations).

Perhaps some quizzes (and especially assignements) could be more challenging?

교육 기관: Iñaki D R

2020년 7월 11일

Great course, excelent professors & simple yet accurate explanations, always guiding you through the course and through practical implementation of acquired knowledge

교육 기관: Thomas K A W

2018년 1월 8일

Great course! I love the instructors and the thoroughly designed structure of their course. The effort they put into this course certainly shines through every video!