Best AI tools for< Housing Policy Analyst >

EliseAI is an industry-leading AI application designed for the housing and healthcare sectors. It offers a comprehensive suite of AI solutions for property management companies, assisting in leasing, maintenance, renewals, and delinquency management. EliseAI streamlines communication across multiple channels, providing personalized, omni-channel support to prospects and residents. The platform automates tasks such as responding to maintenance requests, sending renewal reminders, and reducing delinquencies through automated reminders and follow-ups. With features like voice, text, email, and chat support, EliseAI enhances the prospect-to-resident journey, improving operational efficiency and resident satisfaction.

QuickCasa is an AI-powered platform designed for smarter leasing lead qualification in the real estate industry. It utilizes advanced AI technology to engage, qualify, and convert rental leads, allowing property managers to provide a more personalized and efficient customer experience for prospective residents. QuickCasa offers features such as AI-powered lead scoring, real-time reporting, natural humanlike conversations, and automated lead summary notifications.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Ocrolus is an intelligent document automation software that leverages AI-driven document processing automation with Human-in-the-Loop. It offers capabilities such as classifying, capturing, detecting, and analyzing documents, with use cases in cash flow, income, address, employment, and identity verification. Ocrolus caters to various industries like small business lending, mortgage, consumer finance, and multifamily housing. The platform provides resources for developers, including guides on income verification, fraud detection, and business process automation. Users can explore the API to build innovative customer experiences and make faster and more accurate financial decisions.

Skillsminer is a Workforce Intelligence Platform that helps businesses bridge the growth gap by unlocking dynamic and scalable workforce potential. The platform utilizes AI technology to provide valuable insights and data to identify, develop, and utilize skills and talent effectively. Skillsminer supports various industries such as utilities, financial sector, education, housing associations, health sector, and government in recruiting hidden talent, maximizing internal mobility, and enhancing career opportunities. The platform aims to help businesses hire smarter, improve workforce agility, and make informed learning and development decisions to drive sustainable growth and business success while optimizing costs.

Pollox.ai is an AI-powered platform that serves as the ultimate resource for unrepresented home buyers. It offers comprehensive guides, blog posts, and tools to assist individuals in navigating the complex process of buying a home. With advanced algorithms and data analytics, Pollox.ai provides personalized recommendations and insights to help users make informed decisions throughout their home buying journey.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

AI-PhD-S25 is a mono-repo for the DOTE 6635 course on AI for Business Research at CUHK Business School. The course aims to provide a fundamental understanding of ML/AI concepts and methods relevant to business research, explore applications of ML/AI in business research, and discover cutting-edge AI/ML technologies. The course resources include Google CoLab for code distribution, Jupyter Notebooks, Google Sheets for group tasks, Overleaf template for lecture notes, replication projects, and access to HPC Server compute resource. The course covers topics like AI/ML in business research, deep learning basics, attention mechanisms, transformer models, LLM pretraining, posttraining, causal inference fundamentals, and more.

This repository is a collection of papers on Tabular Large Language Models (LLMs) specialized for processing tabular data. It includes surveys, models, and applications related to table understanding tasks such as Table Question Answering, Table-to-Text, Text-to-SQL, and more. The repository categorizes the papers based on key ideas and provides insights into the advancements in using LLMs for processing diverse tables and fulfilling various tabular tasks based on natural language instructions.

SurveyX is an advanced academic survey automation system that leverages Large Language Models (LLMs) to generate high-quality, domain-specific academic papers and surveys. Users can request comprehensive academic papers or surveys tailored to specific topics by providing a paper title and keywords for literature retrieval. The system streamlines academic research by automating paper creation, saving users time and effort in compiling research content.

AI-on-the-edge-device is a project that enables users to digitize analog water, gas, power, and other meters using an ESP32 board with a supported camera. It integrates Tensorflow Lite for AI processing, offers a small and affordable device with integrated camera and illumination, provides a web interface for administration and control, supports Homeassistant, Influx DB, MQTT, and REST API. The device captures meter images, extracts Regions of Interest (ROIs), runs them through AI for digitization, and allows users to send data to MQTT, InfluxDb, or access it via REST API. The project also includes 3D-printable housing options and tools for logfile management.

Rubix ML is a high-level machine learning and deep learning library for the PHP language. It provides a developer-friendly API with over 40 supervised and unsupervised learning algorithms, support for ETL, preprocessing, and cross-validation. The library is open source and free to use commercially. Rubix ML allows users to build machine learning programs in PHP, covering the entire machine learning life cycle from data processing to training and production. It also offers tutorials and educational content to help users get started with machine learning projects.

The neo is an open source robotics research platform powered by a OnePlus 3 smartphone and an STM32F205-based CAN interface board, housed in a 3d-printed casing with active cooling. It includes NEOS, a stripped down Android ROM, and offers a modern Linux environment for development. The platform leverages the high performance embedded processor and sensor capabilities of modern smartphones at a low cost. A detailed guide is available for easy construction, requiring online shopping and soldering skills. The total cost for building a neo is approximately $700.

AIC Pico is a small and versatile tool designed for emulating various I/O protocols such as Sega AIME I/O, Bandai Namco I/O, and Spicetools CardIO. It supports card types like FeliCa, ISO/IEC 14443 Type A, and ISO/IEC 15693, allowing users to create virtual AIC from Mifare cards. The tool is open-source and easy to integrate into Raspberry Pi Pico projects. It requires skills in 3D printing and soldering tiny components. AIC Pico comes in different variants like PN532, PN5180, AIC Key, and AIC Touch, each with specific assembly instructions and components. The firmware can be updated via UF2 files and offers command line configurations for LED control, brightness adjustment, card detection, and more.

Basalt is a lightweight and flexible CSS framework designed to help developers quickly build responsive and modern websites. It provides a set of pre-designed components and utilities that can be easily customized to create unique and visually appealing web interfaces. With Basalt, developers can save time and effort by leveraging its modular structure and responsive design principles to create professional-looking websites with ease.

AI By Doing is a hands-on artificial intelligence tutorial series that aims to help beginners understand the principles of machine learning and deep learning while providing practical applications. The content covers various supervised and unsupervised learning algorithms, machine learning engineering, deep learning fundamentals, frameworks like TensorFlow and PyTorch, and applications in computer vision and natural language processing. The tutorials are written in Jupyter Notebook format, combining theory, mathematical derivations, and Python code implementations to facilitate learning and understanding.

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment interfaces and libraries for understanding AI systems. It empowers developers and stakeholders to develop and monitor AI responsibly, enabling better data-driven actions. The toolbox includes visualization widgets for model assessment, error analysis, interpretability, fairness assessment, and mitigations library. It also offers a JupyterLab extension for managing machine learning experiments and a library for measuring gender bias in NLP datasets.

This repository provides the official implementation of the paper 'On Embeddings for Numerical Features in Tabular Deep Learning'. It focuses on transforming scalar continuous features into vectors before integrating them into the main backbone of tabular neural networks, showcasing improved performance. The embeddings for continuous features are shown to enhance the performance of tabular DL models and are applicable to various conventional backbones, offering efficiency comparable to Transformer-based models. The repository includes Python packages for practical usage, exploration of metrics and hyperparameters, and reproducing reported results for different algorithms and datasets.

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

MathCoder is a repository focused on enhancing mathematical reasoning by fine-tuning open-source language models to use code for modeling and deriving math equations. It introduces MathCodeInstruct dataset with solutions interleaving natural language, code, and execution results. The repository provides MathCoder models capable of generating code-based solutions for challenging math problems, achieving state-of-the-art scores on MATH and GSM8K datasets. It offers tools for model deployment, inference, and evaluation, along with a citation for referencing the work.

Awesome-Efficient-LLM is a curated list focusing on efficient large language models. It includes topics such as knowledge distillation, network pruning, quantization, inference acceleration, efficient MOE, efficient architecture of LLM, KV cache compression, text compression, low-rank decomposition, hardware/system, tuning, and survey. The repository provides a collection of papers and projects related to improving the efficiency of large language models through various techniques like sparsity, quantization, and compression.

LLM-Synthetic-Data is a repository focused on real-time, fine-grained LLM-Synthetic-Data generation. It includes methods, surveys, and application areas related to synthetic data for language models. The repository covers topics like pre-training, instruction tuning, model collapse, LLM benchmarking, evaluation, and distillation. It also explores application areas such as mathematical reasoning, code generation, text-to-SQL, alignment, reward modeling, long context, weak-to-strong generalization, agent and tool use, vision and language, factuality, federated learning, generative design, and safety.

Specializing in public housing policies and community development insights.

Your assistant in drafting local and state ADU Policy

Fostering transparent dialogue, expert in housing and urban planning.

Finding you a place to live in the era of AI

Transform Your Home Search into an Epic Journey with Choose Your Own Adventure Housing – Where Every Click is a New Path!

A digital housing developer aiding in sustainable house model selection based on local regulations and preferences.

Guidance on UK housing association engagement for upgrades and proposals.

I find housing options for the homeless.

Expert in local real estate, housing, and homelessness advice

Enhance tenant-landlord interactions using a GPT chatbot that provides both parties fast access to housing laws and best practices.

All you need to know - from basics to latest developments e.g. Post Cookie in 2024 , the rise of DOOH, CTV, In-Housing, and much more...

Expert in UK tenant rights and deposit laws

I find apartments for rent in your city.

I’m here to help refugees settle down in their new home, and to support organizations who help them.

Facilitates seamless employee relocation and immigration processes.

Guides users through VA benefits and services.

GPT especializado em buscar e exibir imóveis de um quarto com URLs completos para copiar e colar, e mapas.