Exploratory Data Analysis on Haberman Dataset
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Updated
Oct 29, 2020 - Jupyter Notebook
Exploratory Data Analysis on Haberman Dataset
Strip Plot, Grouping with Strip Plot, Swarm Plot, Box and Violin Plot, placing plots together, Combining the plots, Joint Plot, Density Plot, Pair Plot
Employed hyper-parameter tuning (Gridsearch CV) and ensemble methods (Voting Classifier) to combine the results of the best models. Data Cleaning and Exploration using Pandas. Stratified Cross Validation to model and validate the training data
Used libraries and functions as follows:
This repository contains the file for the task that was done as part of my internship in The Sparks Foundation with specialization - Data Science & Business Analytics.
EDA - Pre processing | Feature Engineering
A simple example on creating violin plots using Seaborn library in Python
Tidy Tuesday: Bench press results by month (men), 1990-2019
The project explores methods like groupby, melt of pandas and infer information from data of patients having cardiovascular disease and healthy individuals.
The objective of this work is to investigate factors affecting borrower rate and loan amount.
Python EDA and Visualization Using , Matplotlib, Seaborn,Plotly and Bokeh. Map visualization using Folium
Visualization using Matplotlib and Seaborn
📘 Ejemplos de gráficos con R
Scripts that I've used during grad school for data collection, analysis, visualization, cleaning, wrangling, etc., for classes, project reports, and manuscripts.
📓 Visualization and training a basic ML model on the Iris dataset
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