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followers: 57.0 following: 12.0 repos: 138.0 gists: 0.0

Name: Mohamed Shaad

Type: User

Company: BrandCollab | Metridash

Bio: Data Scientist @ BrandCollab | Metridash

Blog: https://imshaad.vercel.app/

I'm Mohamed Shaad, Data Scientist from India.

🌱 I’m currently exploring Agentic Automation.
👯 I’m looking to collaborate on Gen AI and NLP Projects.
📫 You can reach me at [email protected].

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Mohamed Shaad's Projects

multiple-disease-prediction-system

The Multiple Disease Prediction project aims to create a user-friendly web application that allows users to input relevant medical information and receive predictions for different diseases.

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.

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.

numpy-exercises

This project provides a collection of Jupyter Notebook exercises for practicing NumPy, a fundamental library for numerical computing in Python. NumPy provides powerful data structures and functions for handling large, multi-dimensional arrays and matrices. Through this project, we aim to enhance our skills in NumPy.

pandas-exercises

This project provides a collection of Jupyter Notebook exercises for practicing pandas, a powerful data manipulation and analysis library in Python. pandas offers a wide range of functions and methods for handling and analyzing structured data. Through this project, we aim to enhance our skills in pandas.

password-strength-checker

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.

personal-website

This repository contains the source code and assets for Mohamed Shaad's personal website. The website showcases Mohamed Shaad's background, skills, and projects as a self-taught data scientist from India.

responsive-website-kawa-space

This project aims to recreate the responsive design of the Kawa Space website.

salary-prediction

This project involves the prediction of salary based on position using Support Vector Regression (SVR) in Jupyter Notebook. The dataset contains information about different positions and their corresponding salaries. Through this analysis, we aim to build a regression model that accurately predicts the salary based on the given position.

scikit-learn-exercises

This project provides a collection of Jupyter Notebook exercises for practicing scikit-learn, a popular machine learning library in Python. Scikit-learn provides a wide range of machine learning algorithms, tools for data preprocessing, model evaluation, and more. Through this project, we aim to enhance our skills in Scikit-learn.

seaborn-exercises

This project provides a collection of Seaborn exercise plots implemented in Jupyter Notebook for practice. Seaborn is a powerful data visualization library in Python that offers a variety of statistical plots and visualization techniques. Through this project, we aim to enhance our skills in data visualization using Seaborn.

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Special Repository

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.

spotify-dataset-analysis-eda-

Exploratory Data Analysis on Spotify Dataset using seaborn plots.

statistics-python

This project provides a collection of Jupyter Notebook exercises for practicing statistics concepts using Python. Statistics is a fundamental field in data analysis and plays a crucial role in understanding and interpreting data. Through this project, we aim to enhance our statistical skills by implementing various concepts using Python.

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.

student-performance-analysis

This project involves the analysis of student performance using Seaborn plots in Jupyter Notebook. The dataset contains information about students' demographics, study habits, and performance in various subjects. Through this analysis, we aim to gain insights into the factors that influence student performance.

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.

wine-quality-prediction

Wine Quality Prediction using Logistic Regression Classification Machine Learning model.

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.

zomato-dataset-analysis

This project involves the analysis of the Zomato dataset for restaurants in Bengaluru city. The dataset provides information about various restaurants, including their ratings, cuisines, costs, and more. Through this analysis, we aim to gain insights into the restaurant landscape in Bengaluru and explore factors that influence ratings.