Popular GitHub Repositories for Housing Affordability

A Python package housing a collection of deep-learning multi-modal data fusion method pipelines! From data loading, to training, to evaluation - fusilli's got you covered ?

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

The "House Price Prediction" project focuses on predicting housing prices using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, and XGBoost, this project provides an end-to-end solution for accurate price estimation.

MLOps Paris Housing Price Prediction.

Explore this GitHub repository housing 3 versions of Falcon code for text generation. Each version leverages distinct libraries and models, enabling diverse approaches to generating textual responses. Discover the possibilities within!

NLP server housing intent and NER models as well as an LLM agent with long term memory vector store for Ditto assistant clients.

A machine learning project that explores and predicts the prices of houses in Washington, USA

This repo uses Natural Langauage Processing, time series analysis, and ARIMA to explore predictive housing trend analysis.

In this repository, a regression analysis is conducted using different machine learning and deep learning models. The study is led in order to choose the most suitable model by looking at different characteristics (models tuning, features scaling, etc).

Time Series Forecasting of the housing price in Queens using the SARIMA, Facebook Prophet, and the LSTM

FoxTrend uses advanced machine learning to provide insightful stock price forecasts and comprehensive company information. The platform also offers additional features, such as car price prediction, loan approval assessment, and housing price estimation.

This repository will contain the code of an end to end ML project of House Price prediction and Housing Property recommendation as per the data scrapped from Magicbricks.com

Bayesian Market Segmentation Algorithm for Hedonic Analysis

Leveraged Machine Learning to perform Time Series Analysis and forecast housing prices in Miami-Dade County. The end goal was to identify and recommend the top 5 zip codes that are predicted to see the highest growth in average home value.

Enhance team collaboration in ML projects using MLflow on AWS. Track experiments, store models, and predict housing prices in California, ensuring reproducibility and effective teamwork.

A curated training dataset for fine-tuning large language models on U.S. affordable housing policy, finance, public housing, LIHTC, regulations, and voucher program administration. Designed for compliance automation, technical assistance, and intelligent document generation in pursuit of affordable housing development and preservation.

PIERRE — Une IA open source, plurilingue et multicanale au service du mouvement HLM, de ses candidats, locataires et collaborateurs

P2P marketplace for Rutgers students selling school items, furniture, housing, etc. -- Generated text embeddings using pretrained Hugging Face NLP transformers & implemented semantic search in the store and faq pages using vector cosine similarity -- Developed a KNN recommendation system

Machine Learning Regression Model with FastAPI