AI-Powered Renovation Cost Estimation for Homeowners & Builders

AI-Powered Renovation Cost Estimation for Homeowners & BuildersAI-Powered Renovation Cost Estimation for Homeowners & Builders

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Minhal Raza

• Feb 17

Ballpark: Fast & Accurate Renovation Cost Tool Ballpark is an AI-driven platform that provides quick and precise cost estimates for construction and renovation projects. It analyzes uploaded images to detect dimensions and materials, then calculates costs using real-time pricing. Users can modify material choices, refine AI outputs, and download detailed PDF reports. Perfect for homeowners, engineers, and builders, Ballpark streamlines budgeting, planning, and informed decision-making.

AI Development Chatbase

Moiz Mansoori

• Apr 1

Built a deployed AI tool that lets users upload research papers and query them using natural language. RAG pipeline with vector search retrieves precise context-aware answers. Features PDF parsing, AI summaries, topic modeling, and citation extraction. Live on Render.

AI Engineer FastAPI LangChain Python AI Development

Istiak Ahmed Khan

• 2d

interesting

Asad Aziz

• Apr 1

🚀 SMS Spam Detection Project

I’m excited to share one of my machine learning projects — an SMS Spam Detection System 📩

🔍 The goal of this project is to automatically classify incoming messages as spam or ham (legitimate messages).

💡 Key Features:

Machine Learning-based model

Text preprocessing & feature extraction

Accurate spam classification

Simple and user-friendly interface using Streamlit

🛠 Technologies Used:

Python

Scikit-learn

Pandas & NumPy

Streamlit

🌐 The project is available on GitHub and also deployed using Streamlit.

📎 Project Link: https://sms-spam-detection-001.streamlit.app/

🙏 Feel free to check it out and share your feedback. Your suggestions will help me improve further!

#MachineLearning #Python #AI #DataScience #Streamlit #GitHub #Learning

AI Development AI Engineer Python scikit-learn Streamlit Machine Learning Engineering

Marco Mastroeni

• Apr 1

Nice work! It seems really interesting. Some time ago i did something similar but for the news online. i sued textblob, nltk and vader for sentiment analysis. Did you use streamlit for the categorization of the words?