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Opiniones y comentarios de aprendices correspondientes a Machine Learning: Regression por parte de Universidad de Washington

5,480 calificaciones

Acerca del Curso

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....

Principales reseñas


16 de mar. de 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!


4 de may. de 2020

Excellent professor. Fundamentals and math are provided as well. Very good notebooks for the’s just that turicreate library that caused some issues, however the course deserves a 5/5

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851 - 875 de 984 revisiones para Machine Learning: Regression

por Matt T

9 de dic. de 2015

I appreciate the nuts and bolts focus on implementation that facilitates development of intuition, intuition that for me at least does not come from presentation of the mathematics in isolation.

por piyush s

21 de feb. de 2016

This is an excellent course to get the math involve behind the regression. Instructors are awesome. I also feel that Bayseain regression should have been included. I missed that part badly.

por fan w

26 de jun. de 2018

when quizs get harder, i'd hope we have more intermediate numbers that we can use to verify with my results. instead of every 5 or 10 steps, maybe it's good to have one every other step.

por Siva J

24 de mar. de 2016

Very challenging course. Could have been 5 had the course duration been stretched by 2 weeks.

Tough to complete and do justice to the subject matter in the time frame provided.

por E. M S

26 de sep. de 2017

Really well presented. Good mix of theoretical and practical. Also, excellent intro course for those with statistics background getting into the machine learning arena

por Reinhardt

4 de feb. de 2018

Some questions in the quiz, regarding the speed needed is not explained in the course. The course gives orders of magnitude while the quizes ask for he exact estimation

por Jose D d O F

13 de sep. de 2017

Assignments were not challenging, I think they could be made harder. The instructor is awesome, though: she is very clear and dives in satisfiable depth on each topic.

por Ahmed E

11 de jun. de 2017

The lecturer is a very skilled presenter that it's difficult to get bored watching the videos. The partially completed code is a great idea, too. Enjoyed this course!

por Pieterjan C

23 de oct. de 2017

In my opnion this course offers a good overview of regression fundamentals and techniques. Like mentioned in the course inference is a topic that is missing.

por Anmol g

14 de nov. de 2016

Nice Course, every concept was explained in necessary details, the quizzes should include questions which should be inferential rather than only output based.


20 de feb. de 2016

A lot of new concepts were introduced with good clarity. All the math was less rigorous which was perfect to understand and get hold on important techniques.

por Suneet T

7 de feb. de 2016

Excellent course to take a deep dive into Regression concepts. Could have been better if the hands on part would have been in R - Programming as well.

por Thakur S S

14 de nov. de 2017

Amazing course, with focus on both theory and application part.

Only problem was the use of GraphLab, would have been lot better if pandas was used


10 de sep. de 2020

Fue un buen curso, pero noté que a veces cambiaban las fórmulas y no explicaban el porqué. Eso me causó mucha confusión y algo de tiempo perdido.

por Nguyễn T T

3 de dic. de 2015

like it so far, after one week

i like the way they let us code the procedures ourselves.

expect it to level up in the upcoming weeks and classes

por James Q

14 de abr. de 2018

Excellent materials. I don't agree with some of the programming principals, but the ML stuff is spot on and I'm using these lessons daily.

por Ayush S

2 de sep. de 2016

Excellent series of courses. Before this was confused what was my interest in Computer Science, now I've found Machine Learning, perfect.

por Kirill D

8 de feb. de 2016

I think you should make update process of Graphlab more intuitive, this was the only problem I have faced during this wonderful course!

por Diego N

31 de ene. de 2016

Better deep understanding of common machine learning concepts. Still learn some different things than those exposed on andrew ng course

por Amirhossein S

13 de ene. de 2019

Well, I think Carlos teaches way more enthusiastically and energetically than Emily! But I did enjoy my course on this specialization.

por Baubak G

23 de may. de 2018

I think the forum activity is a bit low, and I think in some cases the things are overly describes whereas in others it goes too fast.

por Sameer C

25 de jun. de 2016

Overall, the course was really good. But, it would be great if the concept of co-ordinate descent was explained much more clearly.

por RAUL G & F - L & R E

11 de ene. de 2018

Great course - but the exercise and exams are challenging - which is good if you have the programming experience. One really

por Krishna C

18 de ene. de 2016

Its a great course.Please add a module about how to find the significant variables after using all these technologies.

por shashank a

3 de jun. de 2020

Good but needs to updated according to python3, for eq:- print function need brackets in python3 but not python2