Mohamed Shaad's repositories
Password-Strength-Checker-RandomForestClassifier
This project is a password strength checker that utilizes a Random Forest Classifier to determine the strength of a given password. The Random Forest Classifier is trained on a dataset of passwords labeled with their corresponding strength levels.
Heart-Disease-Prediction-KNN
This project focuses on predicting heart disease using the K-Nearest Neighbors (KNN) classification algorithm implemented in a Jupyter Notebook. It aims to provide a tool that can assist in early detection and diagnosis of heart disease based on given input features.
Django-Signup-Adminpanel
This Django project implements an authentication system with user registration, login, logout, and admin functionalities.
Sportsperson-Image-Classifier
This project is an image classifier that can identify different sportspersons using OpenCV, Haar cascades, and logistic regression. The classifier is deployed using Flask, allowing users to interact with it through a web interface.
Cancer-Classification-SupportVectorClassifier
This repository provides a cancer classification model using Support Vector Classifier (SVC). The model aims to classify cancer cases into benign or malignant based on various features obtained from medical examinations.
Movie-Correlation-Analysis
This repository provides a movie correlation analysis using Python. The analysis aims to explore the relationships and correlations between different movie attributes, such as ratings, genres, and revenue.
Future-Sales-Prediction-LinearRegression
This repository provides a sales prediction model using linear regression for an advertising dataset. The model aims to predict sales based on various advertising channels, such as TV, radio, and newspaper.
Diabetic-Patient-Prediction
This project aims to predict diabetic patients using three different classification algorithms: Logistic Regression, Support Vector Classifier, and Random Forest Classifier. The project is implemented using Python and leverages scikit-learn, a popular machine learning library.
Digits-Classification-RandomForestClassifier
This project aims to classify handwritten digits using a random forest classifier algorithm. By analyzing the provided dataset of handwritten digits, the model can accurately predict the digit represented in the image.
Employee-Salary-Prediction-DecisionTreeClassifier
This project aims to predict the salary of employees based on various features using a decision tree classifier algorithm. By analyzing the provided dataset, the model can make accurate predictions if the salaries of new employees is above 100K or not.
Hotel-Booking-Analysis-Python
This project provides an analysis of hotel booking cancellations using Python. It aims to uncover patterns and insights related to hotel booking cancellations and understand the factors that contribute to cancellations in the hospitality industry.
Responsive-Website-Kawa-Space
This project aims to recreate the responsive design of the Kawa Space website.
Netflix-Data-Analysis-Tableau
This project explores the Netflix dataset using Tableau, a powerful data visualization tool. It aims to analyze and visualize various aspects of Netflix's content catalog and provide insights into the streaming platform.
Instagram-Static-Website
This project is a replica of the Instagram homepage, created using HTML and CSS. It provides a static representation of the layout and design of the Instagram login page, including the logo, input fields, buttons, and footer.
Zerodha-Static-Website
This is a clone of the static website of Zerodha, an online stock trading platform. The clone aims to replicate the design and layout of the original website using HTML and CSS.
Django-Clickkart-Ecommerce
This is an E-commerce website built using Django, a Python web framework. It provides a platform for users to browse and purchase products, while also offering various features for both users and administrators.
IPL-Win-Probability-Predictor
The IPL Win Probability Predictor is a web application built using Streamlit. It uses a machine learning model to predict the probability of a team winning an IPL match based on various factors such as batting team, bowling team, host city, target, score, overs completed, and wickets.
Music-Store-Analysis-SQL
This repository contains a collection of SQL queries that can be used to extract information from a database. Each query is designed to solve a specific problem or retrieve specific data. The queries cover various scenarios, including finding the most senior employee, analyzing customer spending, determining popular genres, and more.
Malaria-Detection-Tensorflow
A Flask web application for detecting malaria infection using a pre-trained VGG19 model.
Data-Preprocessing-Pipeline
This project contains a data preprocessing pipeline implemented in Python using the pandas and numpy libraries. The pipeline handles missing values, outliers, and normalizes numeric features in a dataset.
A-B-Testing-CaseStudy
This code performs an A/B testing analysis using control and test group data. It analyzes various metrics such as amount spent, number of impressions, reach, website clicks, searches received, content viewed, added to cart, and purchases. The analysis includes visualizations of the data using Plotly.
Data-ETL-Pipeline
This code demonstrates how to load the Fashion MNIST dataset using TensorFlow's Keras API, preprocess the data, and store it in a SQLite database. The Fashion MNIST dataset consists of grayscale images of clothing items with corresponding labels.
Time-Series-Analysis-Stocks
This is a Streamlit application that performs time series analysis on stocks. It allows users to input a stock ticker symbol and displays various visualizations for the selected stock.
Algorithmic-Trading-Python
This is a Python application that uses the Streamlit library to perform algorithmic trading analysis based on stock momentum. It retrieves stock data from Yahoo Finance using the yfinance library and visualizes the momentum and buying/selling signals using Plotly.
Sarcasm-Detection
This is a web application built using Streamlit that performs sarcasm detection on input text.
Tech-Stocks-Performance-Analysis
This is a web application that allows you to analyze the performance of tech stocks. It retrieves stock data from Yahoo Finance using the yfinance library and visualizes the data using Plotly and Streamlit.
Hate-Speech-Detection
This project implements a hate speech detection model using a decision tree classifier and Twitter data.
Twitter-Hashtag-Analysis
This project provides a website that allows users to analyze real-time tweets from Twitter based on a specific hashtag. The website includes a tweet sentiment analyzer to determine the sentiment (positive, negative, or neutral) of the collected tweets.
Store-Data-Analysis-Excel
This project provides a guide for analyzing store data using Microsoft Excel. It demonstrates how to utilize various Excel features and functions to gain insights into sales, trends, and other key metrics related to store performance.