DEGage is a novel model-based method for gene differential expression analysis between two groups of scRNA-seq count data. It employs a novel family of discrete distributions for describing the difference of two NB distributions (named DOTNB).

This project provides a comprehensive understanding of the Impact of Transportation as a sub-sector responsible for green house gas emissions and its impact on the climate.

Graph-indexed Pandas DataFrames for analyzing hierarchical performance data

This project involves a comprehensive comparative analysis of various machine learning models to classify activities based on a given dataset. The analysis follows a structured approach, including data exploration, model training, model evaluation, and results interpretation to identify the best performing model.

A comparative analysis of various ML models for predicting floods in India, primarily utilizing rainfall data(in mm).

tairaccession python package for interaction with tair and analyzing arabidopsis genome.

This model utilizes regression models and accurately predicts employee salaries based on experience, previous CTC, and job roles, promoting fair salary structures and optimizing resource allocation for streamlined HR operations.

This project employs ensemble learning methods to forecast cybercrime rates, utilizing datasets with population, internet subscriptions, and crime incidents. By analyzing trends and employing metrics like R2 Score and Mean Squared Error, it aims to enhance prediction accuracy and provide insights for effective prevention strategies.

Analyze graph/hierarchical performance data using pandas dataframes

This model utilizes regression models and accurately predicts employee salaries based on experience, previous CTC, and job roles, promoting fair salary structures and optimizing resource allocation for streamlined HR operations.

This project employs ensemble learning methods to forecast cybercrime rates, utilizing datasets with population, internet subscriptions, and crime incidents. By analyzing trends and employing metrics like R2 Score and Mean Squared Error, it aims to enhance prediction accuracy and provide insights for effective prevention strategies.

The DOTNB repository is a collection of code files that implement DOTNB across several programming languages. The DOTNB is the distribution for the Difference Of Two Negative Binomial distributions, i.e., Z=X-Y ~ DOTNB (λ_1,λ_2,p_1,p_2), where X ~ NB(λ_1,p_1 ) and Y ~ NB(λ_2,p_2 ).

Comparison of Binary Diagnostic Tests in a Paired Study Design

The project analyzes global wine production trends from 1835 to 2022, offering insights and forecasts on the industry's evolution for researchers and wine enthusiasts.

A study on the statistical measurement of China's modernization based on the electric vehicle industry chain development

This project focuses on analyzing portfolio returns using Fama-French factors, comparing two distinct investment strategies.

Comparative Data Analysis Ontology - A formalization of concepts and relations relevant to evolutionary comparative analysis

A comparative analysis of 4 ML algorithms. This Hypertension Risk Prediction Model can be described as a machine learning model designed to predict an individual's risk of developing hypertension based on various input parameters.

Explore the cinematic realms with this dynamic Power BI dashboard offering in-depth insights into key performance indicators, financial metrics, and audience reception, enabling a captivating comparison between the iconic Marvel and DC franchises.

This project serves as a hands-on learning experience for practical concepts in JavaScript. The key focus areas in this project include: Object, data structures, Loop structures, Function creation, Comparative, operators.