ai-saas-project---article-summarizer---sumz

analysis-of-car-production-data-set-and-prediction-of-price-using-regression-model

analyzing-absenteeism-in-a-company-using-maching-learning

audiobook-company-customer-acquisition-using-deep-learning

backend_sanity

car-price-prediction-using-machine-learning-with-python

court-hero-backend

crwn-clothing-v2

Version 2 of Crwn-Clothing!

data-structures-and-algorithms

Data Structures and Algorithms in Python

data-structures-and-algorithms--using-java

This repo contains implementation of data structures and algorithms using JAVA

data-structures-and-algorithms-1

diabetes-prediction-using-machine-learning-with-python

Diabetes Prediction Model using Support Vector Machine in Python

dynamic-realtime-animation-control

Our project is targeted at making an application that dynamically detects the user’s expressions and gestures and projects it onto an animation software which then renders a 2D/3D animation realtime that gets broadcasted live.

ecommerce

fake-news-prediction-using-machine-learning-with-python

Fake News Prediction Code using Logistic Regression Model in Python to predict whether the news is fake or real by applying supervised machine learning.

flexit-fitness-app

frontend_react

house-price-prediction-using-machine-learning-with-python

Prediciting the Prices of House using the Boston House Price Dataset by applying the XGBoost Regressor Model

instagram-engagement-rate

kng-clothing-store

linkedin-job-hunter

loan-status-prediction-using-machine-learning-with-python

metalxray

Config files for my GitHub profile.

mnist

monsters-rolodex

Cartoon Monsters Website

monsterville

multiple-disease-prediction-system

phishing-website-detection

A phishing website is a common social engineering method that mimics trustful uniform resource locators (URLs) and webpages.Phishing websites are created to dupe unsuspecting users into thinking they are on a legitimate site. The criminals will spend a lot of time making the site seem as credible as possible and many sites will appear almost indistinguishable from the real thing.The objective of this project is to train machine learning models and deep neural nets on the dataset created to predict phishing websites. Both phishing and benign URLs of websites are gathered to form a dataset and from them required URL and website content-based features are extracted. The performance level of each model is measures and compared. To find the best machine learning algorithm to detect phishing websites.

phonepe-pulse-data-2018-2022-visualization-project

portfolio-3d