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Statistical Data Visualization with Seaborn From UST(으)로 돌아가기

Coursera Project Network의 Statistical Data Visualization with Seaborn From UST 학습자 리뷰 및 피드백

4.6
별점
153개의 평가
32개의 리뷰

강좌 소개

Welcome to this Guided Project on Statistical Data Visualization with Seaborn, From UST. For more than 20 years, UST has worked side by side with the world’s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by their purpose, they partner with clients from design to operation. With this Guided Project from UST, you can quickly build in-demand job skills and expand your career opportunities in the Data Science field. Producing visualizations is an important first step in exploring and analyzing real-world data sets. As such, visualization is an indispensable method in any data scientist's toolbox as well as a powerful tool to identify problems in analyses and for illustrating results. In this project, we will employ the statistical data visualization library, Seaborn, to discover and explore the relationships in the Breast Cancer Wisconsin (Diagnostic) data set. Using the exploratory data analysis (EDA) results from the Breast Cancer Diagnosis – Exploratory Data Analysis Guided Project, you will practice dropping correlated features, implement feature selection and utilize several feature extraction methods including; feature selection with correlation, univariate feature selection, recursive feature elimination, principal component analysis (PCA) and tree based feature selection methods. Lastly, we will build a boosted decision tree classifier with XGBoost to classify tumors as either malignant or benign. By the end of this Guided Project, you should feel more confident about working with data, creating visualizations for data analysis, and have practiced several methods which apply to a Data Scientist’s role. Let's get started!...

최상위 리뷰

JS
2020년 10월 5일

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

HA
2020년 6월 29일

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

필터링 기준:

Statistical Data Visualization with Seaborn From UST의 32개 리뷰 중 1~25

교육 기관: Nagabhairu v k

2020년 5월 14일

Not at all useful

교육 기관: Yaron K

2021년 9월 7일

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).

교육 기관: Suhaimi C

2020년 11월 19일

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.

교육 기관: José P P D D S

2020년 10월 6일

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

교육 기관: HAY a

2020년 6월 30일

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

교육 기관: Aakansha S

2020년 4월 22일

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

교육 기관: Punam P

2020년 5월 13일

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

교육 기관: Jayden P

2021년 6월 24일

Clean and simple. No issues with this course .

교육 기관: SUGUNA M

2020년 11월 19일

Good project based course

교육 기관: Hitesh J

2020년 7월 20일

optimal for beginners

교육 기관: Doss D

2020년 6월 14일

Thank you very much

교육 기관: Suresh B K

2020년 6월 19일

Good experience

교육 기관: Hector P

2020년 9월 13일

Great project!

교육 기관: Adolf Y M

2020년 10월 11일

all is good

교육 기관: Priscila A B

2021년 4월 7일

Perfect!

교육 기관: amarendra k y

2020년 6월 2일

Awesome

교육 기관: Prakhar M

2020년 9월 27일

Good

교육 기관: tale p

2020년 6월 26일

good

교육 기관: p s

2020년 6월 22일

Good

교육 기관: Fhareza A

2020년 9월 14일

wow

교육 기관: Jorge G

2021년 2월 26일

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.

교육 기관: Alex K

2020년 12월 7일

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?

교육 기관: Lilendar R

2020년 8월 9일

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.

교육 기관: Sebastian A T H

2020년 10월 2일

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

교육 기관: Gayatree D

2020년 6월 3일

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