A New Interactive Approach to Learning Data Analysis

This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project

Learned Machine Learning from scratch and take the first step towards AI with Six-week certified training powered by Analytics Vidhya

The project aims to perform various visualizations and provide various insights from the considered Indian automobile dataset by performing data analysis that utilizing machine learning algorithms in R programming language.

This project aims to analyze the AQI data using univariate and bivariate analysis techniques to understand the distribution, trends, and relationships within the data.

Case study to identify risky loan applicants and understand factors that contribute to a loan default.

ASURV: Astronomy SURVival analysis

Udacity - Data Analyst Nanodegree - Project 5 - Data Visualization

Exploratory Data Analysis Theory and Python Code

This repository contains Exploratory Data Analysis in Python on Autism Behavioural Challenges on children(0-18 years) dataset

Summer Training on Machine Learning by Internshala, powered by Analytics Vidhya,

Data Exploration is the initial step in data analysis, where users explore a large data set in an unstructured way to uncover initial patterns, characteristics and points of interest.

This repository contains introductory notebook for logistic regression

The main objective of this project is to build a model to identify whether the delivery of an order will be late or on time.

Udacity Data Analyst Nanodegree - Project V

Stats-Mosaic-Streamlit is a comprehensive GitHub repository that aims to provide a growing collection of curated content and projects centered around statistics and its intersection with data science, machine learning, and artificial intelligence.

Predicting Cryptocurrency Prices with Machine Learning - Time Series Forecasting

Décorticage les jeux de données commerciale pour faciliter la prise de décision appuyée sur data: sortir les business insights, identifier les anomalies et des opportunités