学生对 Coursera Project Network 提供的 Statistical Data Visualization with Seaborn From UST 的评价和反馈

Not at all useful

Shows an example of feature selection using sklearn SelectKBest and RFECV, xgboost plot_importance, and dimensionality reduction using PCA. With seaborn visualizations of EDA and results of running xgboost ML.

The completed notebook is included in the resources, so you can concentrate on learning (rather than on improving your typing skills).

Awesome guided project. Good overview and interesting subject. I learned a lot using python and seaborn for statistical data visualization. Thanks much for offering this guided project. Highly recommend it to take part 1 first, then this part 2.

A machine learning perspective on seaborn capacity, dealing with plots of common results when removing features or selecting important features from dataset

Great course for a beginner to be equipped with data science tools and feature selection methods for machine learning!

Thankyou Sir , for explaining in a very simple way it helps me alot!

Thanks for the course..Nice work and helpful project..

Clean and simple. No issues with this course .

Good project based course

optimal for beginners

Thank you very much

Good experience

Great project!

all is good

Perfect!

Awesome

Good

good

Good

wow

I do not recommend taking this type of course, take one and pass it, however after a few days I have tried to review the material, and my surprise is that it asks me to pay again to be able to review the material. Of course coursera gives me a small discount for having already paid it previously. It is very easy to download the videos and difficult to get hold of the material, but with ingenuity it is possible. Then I recommend uploading them to YouTube and keeping them private for when they want to consult (they avoid legal problems and can share with friends), then they can request a refund.

Good instructor, nice bite sized course design and hands on approach. Only thing is the complexity: I probably lack a bit of the theoretical understanding which makes it a little mystifying what is going on, particularly in the second part of the course. At the same time, if I did have the required background I imagine it might be a little basic?

I think the quizs are very easy, it has to have atleast 10 questions. Beause as we are provided with the jupyter notebook we are understanding everything in detail and expecting some good no of questions in the quiz.

Un excelente curso para profundizar en habilidades prácticas tanto en temas de seaborn como en sklearn

The course was really nice however, I faced little issues while connecting to the rhyme desktop.