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    Back to Machine Learning: Regression

    Learner Reviews & Feedback for Machine Learning: Regression by University of Washington

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    4.8
    stars
    5,576 ratings

    About the Course

    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 feature...
    ...

    Top reviews

    EV

    Jun 25, 2016

    Filled StarFilled StarFilled StarFilled StarFilled Star

    An in-depth overview of the regression techniques and models. I think it went as deep into the concepts as I wanted it to go. Being a developer I found it quite understandable, and useful.Keep it up!

    PD

    Mar 17, 2016

    Filled StarFilled StarFilled StarFilled StarFilled Star

    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!

    Filter by:

    151 - 175 of 1,000 Reviews for Machine Learning: Regression

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    By Manoj K

    •

    Feb 8, 2016

    Wow.... to complete this course, one really needs to work hard... one of the best teachers and the way they build concepts, so easy and systematic... thanks you so much for making me learn some of the challenging concepts with ease...

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Sundar J D

    •

    Feb 7, 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.

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    By Erik R

    •

    May 23, 2017

    A really nice course, explanations in the videos are absolutely clear. I do have to say, however, that I was hoping to go into kernel-based regression a bit further. But overall, a great course which i definitely recommend to others!

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    By Brian B

    •

    Jan 11, 2016

    One of the top Coursera courses I've had the pleasure of taking!

    The instructors do a great job of making the math understandable (although I am a graduate student in applied math, so the mathy parts of machine learning aren't new).

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    By Nitin K M

    •

    Sep 12, 2019

    Highly recommend this course if anyone wants to truly understand the stats used behind regression. Professor Emily has taught this specialization in the best way possible. Thank you Cousera for providing such specialization online.

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    By Ziyue Z

    •

    Aug 10, 2016

    Great course! Excellent overview of the goal of regression, and the difference between L1 and L2 regularization, as well as some generally applicable machine learning concepts/algorithms. Packed with material and very worthwhile.

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    By Xiaoxuan G

    •

    Jul 12, 2022

    This is the best course ever. Very clear and straightforward, all the materials included should be required while other instructors just told you how to use it without explicitly explain everything in detail. EXCELLENT COURSE!

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Fakrudeen A A

    •

    Aug 26, 2018

    Excellent course and requires some hardwork during weekends but pays off very well. It teaches Liner Regression, regularization, loss fn and k-NN among others - all very important ML concepts.

    Thank you to excellent teachers!

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    By Tyler B

    •

    Jan 1, 2016

    Excellent course on Regression! From the basics up to some pretty complicated stuff, Emily Fox did a great job explaining the concepts and the programming assignments were challenging without being overwhelming. Well done!

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    By SMRUTI R D

    •

    Feb 15, 2016

    A very detailed course on regression with real data examples and which exposes the student to actual coding of different functions, rather than using already available functions. I got a very satisfying learning experience.

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    By dharmesh s

    •

    Feb 8, 2020

    this course is excellent for me .it gives me a deeper understanding of algorithms and concepts. this course also gives me direction to my career . thanks coursera and university of washington for providing such platform .

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Xun Y

    •

    Feb 16, 2020

    Very informative course. The best part is the visualization of ridge regression and lasso regression optimization. It would be great if the professor can add one final project to walk through the entire modeling process.

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    By Manuel G

    •

    Jan 1, 2019

    Amazing course! Thoroughly enjoyed it, and really appreciated the level of detail in some of the theoretical concepts. Yet it also stayed within what's practically useful and had a good amount of hands-on implementation.

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    By Trung B T

    •

    Jan 17, 2016

    What a great course about machine learning I've been taken so far! One of the best thing (I like) for this course is that I have deep understanding and I am able to implement the machine learning algorithms by myself.

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    By Aarshay J

    •

    Mar 9, 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.

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    By 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!

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    By Neo P

    •

    Dec 19, 2021

    The ability of this prof to convey these complex concepts simply is astonishing. I've taken over 50 data analysis/science online courses and this is in the top 3 for sure. One thing though: why not just use Pandas?

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    By Rajesh P

    •

    Dec 30, 2015

    I really got a lot of the course. The material is explained very well. The programming assignments helped further the understanding. The recap video that summarizes the entire module in 10-15 min is also very good.

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    By shoubhik b

    •

    Jan 31, 2017

    Very thorough. If you are beginner this course will give you the tools to do further study by yourself. I still go back to the lectures to refresh a few concept. Really sad that course 5 and 6 won't be released :(

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Michael H

    •

    Sep 2, 2016

    Fantastic course. Perfect balance of practice and theory. I have tried learning regression a number of times now and after doing this course I feel like I finally have a good grasp on it. Absolutely no complaints.

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    By Yu I

    •

    Aug 4, 2016

    This course was super exciting! The explanation was very intuitive, using nice visualizations. The programming assignments was really practical. It would be great for machine learning newbees to learn regression.

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    By Yang X

    •

    Feb 14, 2016

    Love this course! Love the flexibility of the course but if rigor is what you want, they offer mathematical rigor in optional lectures as well. Great lectures and well-designed assignments. Highly recommended

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    By Ad T

    •

    Jul 17, 2017

    Great course with just the right level of detail. Had lots of fun implementing the algorithms in Python based on the instructions and all the examples helped really understand what is happening under the hood.

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    By Fernando F

    •

    Jan 12, 2016

    I think this course has been very interesting. Regression is too wide for covering entirely in a course like this but it has provided me with the basic knowledge and fundamentals to keep working in the matter.

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    By Stephen M

    •

    Jan 23, 2018

    I enjoyed the math and the Python exercises, which were interesting and challenging. The functions and algorithms used in the notebooks would be a good starting point for a set of Python regression classes.

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