ziyad
@muhammed-ziyad-777AI Data Engineer | Aspiring AI Data Scientist š Studying AI | š” Passionate About Data Science Exploring AI algorithms, machine learning, and data-driven sol
Language Breakdown
Lines of code distribution across 6 owned repositories
I-Shaped Developer
I-shapedSpecialist ā deep expertise in Jupyter Notebook
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Repos
8
PRs
0
Growth
+18%
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Coding Streak
Contribution activity over the past year
NOOR MUHAMMED ANWER M
@noormuhammed4004
Nisam
@niz4mm
Muhammed Afthab PT
@Afthab29
Mhd Irfan
@Irfan635
mhd-nabeel
@mhd-nabeel
Top Repositories
Benchmark tests supporting the openalpr library
This repository serves as a personal collection of projects and resources developed by Vishnu. It showcases a variety of coding projects and practical applications across multiple domains, demonstrating proficiency in languages such as Python, Java, and C.
A machine learning-based web app that predicts real estate prices using features like location, area, and bedrooms. Built with Flask and Random Forest, it includes a compare-locations feature to help users analyze property trends. Ideal for buyers, sellers, and analysts.
Config files for my GitHub profile.
š Food Price Prediction Using Machine Learning A machine learning project that predicts future food prices based on historical data. It utilizes regression models, data preprocessing, and exploratory data analysis to uncover trends and improve forecasting accuracy. Ideal for helping consumers and businesses anticipate market fluctuations.
This project focuses on basic data visualization using Python's matplotlib and data manipulation with pandas. It demonstrates how to create various types of plots such as bar graphs, pie charts, and histograms from structured data. The project is ideal for beginners looking to understand how to visualize and analyze data using Python.
This project explores and analyzes a dataset of house prices in Bengaluru, India, using Exploratory Data Analysis (EDA) techniques. The goal is to understand key factors affecting housing prices, clean and visualize the data, and prepare it for predictive modeling.
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