Machine Learning

I thoroughly enjoyed the course and learned important machine learning concepts through it.

Even though I had taken already other classes in regression, like Statistical inference or Machine learning from Stanford, this course provided me much better understanding about the variance and bias of a model, as well as, how the the true error and test error is related.

Best Course To Learn Regression Fundamentals Of Machine Learning.

Also, excellent intro course for those with statistics background getting into the machine learning arena good I enrolled in this specialization to learn machine learning using GraphLab Create.

The course is really good for people planning to step into machine learning field.

Great course to get started in the Machine learning , it covers each and every concept of Regression .

All the concepts are explained in so simple way that even a high school kid wont have any trouble understanding Machine learning .

I took Ng's original ML coursera course, and it was good, but this one was much more involved and helped me better understand essential concepts in machine learning and data science.

In order to mimic real-world machine learning problems, we should be required to clean the data and answer open-ended questions that require exploring and understanding the data before developing machine learning models to extract usable information.

This course gave me full concept of the technique of machine learning-Regression.

Very solid course for understanding machine learning principles, including developing methodical approaches to solving data problems.

would recommend for anyone looking to get into data science/ machine learning.

This one contained so much more information than I expected Excelent course, I highly recommend for those who are willing to learn machine learning from the basis, this module (linear regression) covered very important parts that I used to struggle to learn Nice explanation and nice tasks but the course is designed for graphlab.

Highly recommend Ce cours est une excellente opportunité d'appréhender par la pratique les concepts fondamentaux de la régression statistique, et de pouvoir les mobiliser dans une optique prédictive.

What I was trying to get at my starting stage in ML for last 2 months, this course given in 2 weeks.Thank you coursera Good learning materials Highly recommend this course if anyone wants to truly understand the stats used behind regression.

Highly recommend it!

Looking forward to the next one.

Looking forward to the classification course.

Looking forward to the next course!

I am really looking forward to the next class - that's probably the area I would like this series to improve, the gaps between courses are just too long.Overall great work!Thanks!

Looking forward to the three courses in this specialization.

very well structured, the right amount of math and driven by the experiments on the real data.Looking forward to Classification course and others in series.

I'm very much looking forward to the next course in the specialization.

I am looking forward to the next one.

Thank you for a good lecture.The material was excellent and explanation was quite detailed and easy to understand.Some of the programming was a little bit tricky, but I was able to pull through.Thank you again for your efforts and I am looking forward to seeing you in the next course nice Great course, great material Very good for beginners excellent course .

Highly recommended Superb!!

Very thorough and challenging class.Highly recommended.

Overall, highly recommended.

I already knew how to do linear regression before taking this course; however, I had always struggled to understand how ridge and lasso regression worked and what their usefulness was; thanks to this course I was finally able to understand those concepts very well.

The visual explanation of how the ridge and lasso regression work made this course well worth its time.

It does not simply stop with simple linear regression but also tackles ridge and lasso regression using Python notebooks.

From University of Washington I have expected the same.

thanks coursera and university of washington for providing such platform .

Excellent Tutorial Excellent course on Regression by University of Washington One of the best hands on course on ML.

Still learn some different things than those exposed on andrew ng course Excellent!

As much as I love Andrew Ng's Machine Learning course, you could take this sequence instead and get more explanation with the same mathematical rigor.

I took and finished Andrew Ng ML course before and I though I 'now i know something about ML', after finishing this course I feel less confident and I can see how many things there are ahead to learn.

Quite often, in blogs and reviews, Andrew Ng's course (at Stanford) is mentioned as the reference, to me it looks like these series of courses can match Ng's course on machine learning (using Octave).

My favourite machine learning course since Andrew Ng's class.

even better than Andrew NG.

Best course in data science out there.

By far the best Data Science / Machine Learning series I have taken thus far on Coursera.

An extremely valuable course for someone who wants to use these for a data science application but also wants to understand the mathematics and statistics behind them to an appreciable degree.

Mandatory course for every data science begginer.

On the otThis course has interesting contents about regression algorithms but sometimes it goes into too many mathematical details and it is easy to get lost.

On the other hand, as in the previous course, the material has not been updated to reflect that the last courses of the specialty have been canceled.This course has interesting contents about the regression algorithms but sometimes it goes into too many mathematical details and it is easy to get lost.

On the other hand, as in the previous academic year, the material has not been updated to reflect that the last courses of the specialty have been canceled.her hand, as in the previous academic year, the material has not been updated to reflect that the last courses of the specialty have been canceled.This course has interesting contents about the regression algorithms but sometimes it goes into too many mathematical details and it is easy to get lost.

Lectures are clear and interesting, sometimes a little bit too slow but I do suggest to put them in 1.5x in those cases.

little bit disappointed from the decision of not continuing Recommended systems and capstone project.

I did little bit struggle with Python but now I am a bot more confident to take on advanced programming in Python.Thank you very much for offering course.

The quiz questions was a Little bit tricky, I misunderstood the questions and answered on the wrong data set.

I love the case study methodology that clarified all my confusion remained after attending the class.

Course was made very intuitive & easy to understand with a case study based approach Excellent course, challenging but very good learning!

The case study approach followed by the instructors makes it ideal to learn how these ideas used in real-life problems.

Teaching the methods using a case study yields for great illustrations of the concepts.

Amazing course, I enjoined the talking about the linear model, regularization, gradient descent in how to optimize the weights .

I highly recommend the specialisation so far (this is my second course) Actually implemented Gradient Descent, Ridge Regression, Lasso etc.!!!

But I have to admit, I found it very helpful when Emily went into the proofs and theory behind tools such as gradient descent.

The closed-form calculation and comparison against gradient descent is excellent.