Arjun 's Projects
Prediction of income using model's and predicting their accuracy
EDA Analysis and Price prediction of Istanbul Airbnb
The project spans through the dataset and make analysis based on the parameters and models are evaluated to check the accuracy.
Config files for my GitHub profile.
The best model is determined using PCA evaluation for the Arrhythmia prediction
Discover the potential of BERT model through fine-tuning and Q&A applications in this repository
Feature engineering synopsis
The code describes the basic BMI calculation using elif statements. The code displays whether a person is under-weight, healthy or overweight according to the BMI chart
Analysis and prediction of Breast Cancer using several models and classifications
Model analysis of car prices among various parameters
Chainlit's cookbook repo
Detection of Credit_card flaws and analysis through various models
Analyse how member rider's and casual rider's behave differently. Support stakeholders in making data-driven decisions to develop campaigns or strategies aimed at converting casual riders into Cyclistic members.
Predict the model using KNN and Navie Bayes and finding their accuracy score
The analysis is used to predict the fetal health based on various input parameters
The project analyze the various parameters of the flight data and correlate each data's present and a pattern is formed to evaluate the price
Analysis and EDA of GOI-Budget and its distribution to various departments.
Prediction of the gold prices and comparing the values predicted by the models
The GPT-based Universal Web Scraper MVP is a solution that leverages GPT models and web scraping libraries to generate scraper code based on user input and website analysis, simplifying the web scraping process.
Iris flower EDA and plotting the parameters
The project is based on deep learning which detects the lane in road and suggest the user/EMI of car to drive as per the lane presence.
Analyses the lung cancer among the various parameter's of the patient.
Migraine classification model accuracy prediction and its classification report is evaluated.
Analysis of the trend in mobile price based on its various features and the price escalation implied based on it
The code analyses the movie dataset and suggest user the recommended movies based on the user's favorite movie's
build across the different machine learning models that will detect if the mushroom is edible or poisonous by its specifications like cap shape, cap color, gill color, etc. using different classifiers.
Analysis of Netflix, Amazon and Disney