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Statistical Data Visualization with Seaborn From UST に戻る

Coursera Project Network による Statistical Data Visualization with Seaborn From UST の受講者のレビューおよびフィードバック

4.7
158件の評価
32件のレビュー

コースについて

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!...

人気のレビュー

JS
2020年10月5日

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

HA
2020年6月29日

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

フィルター:

Statistical Data Visualization with Seaborn From UST: 1 - 25 / 32 レビュー

by Nagabhairu v k

2020年5月14日

Not at all useful

by Yaron K

2021年9月7日

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).

by Suhaimi C

2020年11月19日

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.

by José P P D D S

2020年10月6日

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

by HAY a

2020年6月30日

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

by Aakansha S

2020年4月22日

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

by Punam R P

2020年5月13日

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

by Jayden P

2021年6月24日

Clean and simple. No issues with this course .

by SUGUNA M

2020年11月19日

Good project based course

by Hitesh J

2020年7月20日

optimal for beginners

by Doss D

2020年6月14日

Thank you very much

by Suresh B K

2020年6月19日

Good experience

by Hector P

2020年9月13日

Great project!

by Adolf Y M

2020年10月11日

all is good

by Pris A

2021年4月7日

Perfect!

by amarendra k y

2020年6月2日

Awesome

by Prakhar M

2020年9月27日

Good

by tale p

2020年6月26日

good

by p s

2020年6月22日

Good

by Fhareza A

2020年9月14日

wow

by Jorge G

2021年2月26日

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.

by Alex K

2020年12月7日

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?

by Lilendar R

2020年8月9日

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.

by Sebastian A T H

2020年10月2日

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

by Gayatree D

2020年6月3日

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