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Machine Learning: Regression(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
별점
5,168개의 평가
971개의 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!

KM

May 05, 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

필터링 기준:

Machine Learning: Regression의 939개 리뷰 중 176~200

교육 기관: Chia-Sheng L

Jan 04, 2016

This course offer many aspects like graphic comparison or detail math explanation help us understand more easily what a model or method means. The teacher have great effort on material design.

교육 기관: Carlos S M L

Aug 22, 2020

Un excelente curso que nos introduce a este interesante tema de la regresión. Demasiado útil y explícito a la hora de abordar los temas, realmente fue una gran experiencia. Super recomendado.

교육 기관: Anuj S

Apr 28, 2020

One of the best course on Coursera to learn about Regression with great explanations in mathematics as well as programming. Great analogy used which helps in learning much faster and longer.

교육 기관: Prashant M

Sep 30, 2017

This was a very satisying course with the intensity and queries that challenge me and wish to learn more. I am quite excited to learn more with the new ML bug that has caught me! Liberating.

교육 기관: Wenxin X

Mar 12, 2016

Learned a lot! Now I have been acquired a basic understanding of machine learning! Materials are not much, so it's not painful to accept. Recommended for everybody interested in this topic!

교육 기관: Gustavo K A

Jan 08, 2016

I had the clear sense of actually learning and not just "copying & pasting" bits of code. The questions and problems are challenging enough to make you stop and think about you just learned.

교육 기관: Sergey M

Jan 19, 2016

A very good course! Especially that scikit-learn can be used as framework for solving assignments and at the same time exercises for programming of learning algorithms from scratch. Thanks!

교육 기관: Bilkan E

Oct 16, 2016

Incredible course!

Very good, intuitive and simple introduction to general use machine learning and optimization techniques. I am already employing techniques learned here to my daily work.

교육 기관: vivek s

Aug 31, 2016

it's a nice course. I have learnt many new concepts. I am from information systems background and want my career towards data science. This course helped me a lot in learning new concepts.

교육 기관: Sekhar K

Apr 02, 2017

This course is phenomenal! I am learning a great deal. Dr. Emily Cox is fantastic with her slides, explanation and the way she (and Dr. Carlos Guestrin) structured the course. Loving it!

교육 기관: Ling Z

Apr 09, 2019

I took this class long time ago and just revisited it today. Compared to other online class, this class has a lot details. I am satisfied with both the clarity and depth of the content.

교육 기관: Fabio P

Apr 03, 2016

I really like the learning approach in this course: at first you learn how to use the algorithm and after that you learn how to implement it yourself. That way it's never disappointing.

교육 기관: George P

May 16, 2017

Straight to the point and with useful material to check back whenever you feel is necessary. Learning but also good annotated notes in order to revise things later are very important.

교육 기관: Zachary C

Apr 30, 2017

the professor does an excellent job explain the subject thoroughly, including good in depth descriptions of matrix algebra and how it applies to things like multi-variable regression.

교육 기관: Alexander T

Dec 30, 2015

A very comprehensive course that covers not only regression, but all base Machine Learning concept. Thanks to Emily, she explains rather complicated topics in a clear and concise way.

교육 기관: Ben K

Feb 23, 2016

Lasso, l2 regularization, ridge regression, etc. - appropriate level of technical detail, first principles discussion, etc. means that a lot of good info was packed into this course.

교육 기관: Vibhutesh K S

May 20, 2019

This is indeed a good course. Covering even much more than I had previously expected. The instructions were quite clear to me and the programming assignments were quite interesting.

교육 기관: Nitish V

Sep 25, 2017

The course is really good for people planning to step into machine learning field. Not so deep , but covers all the relevant topics. Thanks to instructor for making it look so easy.

교육 기관: Alfredo A M S

Jun 27, 2016

Started a little slow, and it may seem repetitive if you see all videos from one week in one day, otherwise I feel it has a good pace.The content was interesting and well explained.

교육 기관: Borna J

Jun 19, 2016

I love everything about this course. the course material is easy to follow. I also like the coding exercises. I highly recommend the specialisation so far (this is my second course)

교육 기관: Girish

Aug 06, 2020

The instructors take care to teach every concept as precisely and intuitively as possible. The assignments are challenging and make sure you learn and internalize the concepts well

교육 기관: Charlotte B

Jul 24, 2019

I definitely learned a lot in this class about different techniques and ways to use regression in machine learning. I also feel like I learned a lot about how to program in Python.

교육 기관: Liang-Yao W

Jun 26, 2017

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 M

Jun 23, 2017

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

Sep 30, 2016

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.