Analytics & Machine Learning R Sidekick
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Updated
Jun 3, 2024 - R
Analytics & Machine Learning R Sidekick
A tool to get a custom report on your Disney comics collection from the Inducks.
Get a detailed report on Flashpoint games from a playlist or that you have played.
To understand and process the data coming out of data engineering pipelines: Clean, sanitize and manipulate data to get useful features out of raw fields
To perform hypothesis testing to find out the variables that are significant in predicting the demand for shared electric cycles in the Indian market
Analysing customer purchasing behaviour against the customer's gender and various other factors to help the business make better decisions.
Generating (divergent) bar plots of attitudes towards transport policy in Switzerland from the Mobility and Transport Microcensus (MTMC)
Data Analysis Practice Repository
A Python library for calculating a large variety of metrics from text
This repository explores the activation patterns of A2 noradrenergic neurons in fear-conditioned rats, using statistical analyses like t-tests and linear regression in R. It focuses on the differences in dopamine β-hydroxylase (DbH) neuron activation between various environmental conditions.
Se realiza un análisis estadístico descriptivo de datos obtenidos en 3 viñedos diferentes con el objetivo de encontrar diferencias y relaciones entre las variables medidas, para concluir las características del vino de cada viñedo.
Um repositório em Python para armazenar códigos de exercícios da disciplina Análise de Dados e Big Data. Também, está presente o trabalho da disciplina, feito com o Jupyter Notebook.
EXCELR ALL ASSIGNMENTS
An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
Easy and thorough description of datasets
Here I'm sharing my projects in data analysis.
Prediction the exited in bank using Artificial Neural Network and Random Forest Classifier.
This repository presents a study on predicting student alcoholism and academic performance using machine learning. By analyzing a dataset of student attributes, we develop models to forecast academic outcomes and alcohol usage.
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