Machine Learning: Regression(으)로 돌아가기

4.8

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825개의 리뷰

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....

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!

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:

교육 기관: Anirudh N

•Jan 09, 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!

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: Priyesh R

•Nov 12, 2016

Awesome course and awesome instructor.

교육 기관: isanco

•Jan 25, 2016

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

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

교육 기관: Chase M

•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!

교육 기관: Min K

•Sep 14, 2017

Thank you very much to Instructor "Emily and Carlos" for such an excellent and very informative course on regression :)

교육 기관: Anaís G

•Apr 22, 2016

great course!

교육 기관: Anindya S

•Jan 02, 2016

Dr. Carlos Guestrin and Dr. Emily Fox are amazing. Needless to say, their way of teaching is absolutely brilliant and fun to learn, concepts which took me few days to learn now takes an hour or so, this is primarily due to their mastery on the subject matter and their lucid way of teaching.

교육 기관: Sundar J D

•Feb 07, 2016

Great course and great instructor. Course covers regression models in great detail. The instructor's explanation of concepts and intuition behind why things are the way they are was really helpful to learn and appreciate the concepts.

교육 기관: YEH T P

•Mar 11, 2017

This is an amazing tour about regression and machine learning. You will learn basic linear regression first and dig into some practical problem include overfitting, feature selection, cross validation, this is a great course for people who interested in machine learning and have basic programming skill.

교육 기관: Carlos D M

•Jan 18, 2016

The topics are presented in a meaningful and understandable way. With enough detail, clarity, and fun. The instructors are super sweet and their dynamics in front of the camera are very inspiring.

The assignments are amazingly well designed. I get to practice the theory I learn from the lectures which truly reinforces what we review.

Even though I don't use the alternative tools (like Pandas), I appreciate that the organizers of the class prepare files and data sets for people who use those tools.

Another thing that's really valuable to me its' the fact that assignments (data, instructions, Jupyter, etc.) can be worked on completely offline and only need Internet connectivity to post results. Because all we do is enter numbers and select a few options, I have successfully submitted my assignments 10 minutes away from boarding a plane. I have had the chance work while riding a car (not driving it, LOL) or in an airplane. Because I have a full-time job, this is a HUGE advantage.

교육 기관: Fabricio N

•Mar 27, 2016

Best course in data science out there.

교육 기관: Pantelis H

•Apr 07, 2016

This is an excellent course. The presentation is clear, the graphs are very informative, the homework is well-structured and it does not beat around the bush with unnecessary theoretical tangents.

교육 기관: Tobi L

•Jan 12, 2016

There was way more interesting mathematics to linear regression than I ever imagined. I thought this was going to be a boring review of linear algebra and quadratic polynomials. I have never been so happy to be wrong!

교육 기관: Carlos L C

•Jan 19, 2016

I learned a lot! Thanks

교육 기관: Sushil P B

•Sep 08, 2016

Well organised. In depth optional lectures help you learn more about the theoretical foundations. Recommended.

교육 기관: Jarun N

•Dec 23, 2015

concise and practical

교육 기관: Renato R S

•Feb 19, 2016

A very well designed course. I would recommend to anyone with serious goals on learning regression and machine learning.

교육 기관: Deleted A

•Nov 21, 2016

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

교육 기관: Gaurav K J

•Apr 22, 2018

I want to

교육 기관: Alejandro G L

•Jan 17, 2016

It is an excellent course.

교육 기관: Jaiyam S

•Jan 01, 2016

This is one of the best online courses out there and not just about Machine Learning. The course was very well organized and the teaching staff was very helpful in resolving whatever issues cropped up. I would suggest you to provide additional readings/ references at the end of the course in 'Closing remarks'. Thank you Profs. Emily and Carlos for the wonderful course. Keep up the good work! I am looking forward to the next one.

교육 기관: Aarshay J

•Mar 09, 2016

A very good starting to the journey to Machine Learning. Just one disappointment, I was expecting the classification and clustering courses to start together but the specialization has been delayed by a long time now.

교육 기관: Paul C

•Aug 13, 2016

This Machine Learning class and the rest of the Machine Learning series from the University of Washington is the best material on the subject matter. What really sets this course and series apart is the case-base methodology as well as in-depth technical subject matter. Specifically, the step through coding of the algorithms provides key insight that is seriously missed in other classes even in traditional academic settings. I highly encourage the authors and other Coursera publishers to continue to publish more educational material in the same framework.

교육 기관: Ahmed M M

•Sep 07, 2016

awesome course, really i loved it