Python Data Visualization using Seaborn - Intermediate

[mitsumi]

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 9 lectures (1 hour, 12 mins) | Size: 630 MB

Be proficient with seaborn technology that is widely used for statistical data visualization techniques

What you'll learn

Under this part of the training program, advanced concepts of seaborn tool that are an introduction to seaborn advance, building structure multiDescription grids, conditional small multiplies, use of custom functions, Descriptionting pairwise data relationships, choosing color palettes, use of different seaborn figure styles, setting different color palettes, use of reference files in advance, etc.
This part of the training program what we learn about intermediate functionalities of seaborn which includes Descriptionting univariate distribution, clotting of bivariate distributions, visualizing linear relationships, functions to draw linear regression models, filtering different kinds of models, conditioning all other variables, join Description and LM Description, use of reference files, KDE Description, etc.

Course
Requirements

Basic knowledge about Data and analytics and Python programming would be preferable
Anyone serious about learning Data Visualization and wants to make a career in this Field

Description

With this course, any sort of tradings or tutorial the efficiency of the training increases drastically is it provides a space for the learners to experiment and everywhere their knowledge in real-time scenarios which helps them understand the concepts in a better way. Different techniques and tools are involved in this training to increase the utility and efficiency of the program. skills that are part of this training program are as follows:

Visualizing the Distribution of a Dataset

Descriptionting Univariate Distributions

Descriptionting Bivariate Distributions

Visualizing Linear Relationships

Functions to Draw linear Regression Models

Fitting Different Kinds of Models

Conditioning on Other Variables

Examples on KDEDescription

Examples on PAIRDescription

JOINTDescription and LMDescription

Under this part of the training program, advanced concepts of seaborn tool that are an introduction to seaborn advance, building structure multiDescription grids, conditional small multiplies, use of custom functions, Descriptionting pairwise data relationships, choosing color palettes, use of different seaborn figure styles, setting different color palettes, use of reference files in advance, etc.

This part of the training program what we learn about intermediate functionalities of seaborn which includes Descriptionting univariate distribution, clotting of bivariate distributions, visualizing linear relationships, functions to draw linear regression models, filtering different kinds of models, conditioning all other variables, join Description and LM Description, use of reference files, KDE Description, etc.

Who this course is for:

The target audience becomes anybody who is interested in learning this Python Seaborn Tutorial and follows the above-mentioned pre-requisites
software engineers, testers
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