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學生對 华盛顿大学 提供的 Machine Learning: Regression 的評價和反饋

5,480 個評分


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....




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!



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


851 - Machine Learning: Regression 的 875 個評論(共 984 個)

創建者 Matt T


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.

創建者 piyush s


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.

創建者 fan w


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.

創建者 Siva J


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.

創建者 E. M S


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

創建者 Reinhardt


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

創建者 Jose D d O F


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.

創建者 Ahmed E


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!

創建者 Pieterjan C


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.

創建者 Anmol g


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



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.

創建者 Suneet T


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.

創建者 Thakur S S


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



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.

創建者 Nguyễn T T


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

創建者 James Q


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.

創建者 Ayush S


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

創建者 Kirill D


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

創建者 Diego N


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

創建者 Amirhossein S


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

創建者 Baubak G


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.

創建者 Sameer C


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

創建者 RAUL G & F - L & R E


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

創建者 Krishna C


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

創建者 shashank a


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