Beautiful ridgeline plots in Python

Seaborn is one of the go-to tools for statistical data visualization in python. It has been actively developed since 2012 and in July 2018, the author released version 0.9. This version of Seaborn has several new plotting features, API changes and documentation updates which combine to enhance an already great library. This article will walk thr…

Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Mo…

Q 21) Check whether the data follows normal distribution a) Check whether the MPG of Cars follows Normal Distribution

Check Whether the Adipose Tissue (AT) and Waist Circumference(Waist) from wc-at data set follows Normal Distribution

Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data. EDA and data visualization, Correlation Analysis, Model Building, Model Testing, Model Prediction.

Supervised-ML---Simple-Linear-Regression---Newspaper-data. EDA and Visualization, Correlation Analysis, Model Building, Model Testing, Model predictions.

Higher Diploma in Science in Computing (Data Analytics) - Programme Module: Fundamentals of Data Analysis (COMP08050)

Visualization using Matplotlib and Seaborn

Normal-Distribution

Suppose GMAT scores can be reasonably modeled using a normal distribution with mean=711 and SD = 29. What is P(X<=680) What is P(697<=X<=740)

Python matplotlib, seaborn and plotly plots cheat sheet

Comparison between Marvel and DC in terms of their Characters Popularity, their Gender, Hair Color, Eye Color, Character Alignment, Appearances, Launch day, names, etc. I have used Seaborn, matplotlib, networkx, and plotly to visualize Interactive plots

Seaborn Visualization on Titanic Dataset Visual exploration of different features on No. of people survived or otherwise Visualization using FacetGrid function, Lambda function and criterion function Visualization of subplots

Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi

👩🏻‍🍳🍽️Restaurant Success Prediction using ML

Q 21) Check whether the data follows normal distribution a) Check whether the MPG of Cars follows Normal Distribution Dataset: Cars.csv

Used libraries and functions as follows:

🧑🏻‍✈✈️Flight Price Prediction using ML