tommanzur
Python developer and data scientist with a PhD in sociology. Passionate about leveraging data to drive insights and solutions.
Pinned Repositories
ArguBot
ArguBot is a chatbot based on the doctoral thesis "Construction of Arguments and Socio-Technical Controversies" by Tomás Manzur. It offers interactive access to the thesis's insights on the Plan Provincial de Ordenamiento Territorial of Mendoza.
autogen_groupchat_RAG
This project demonstrates a group chat system powered by Retrieval Augmented Generation (RAG), utilizing the `autogen` library. It showcases how conversational agents, powered by llms, tools, or human inputs, can perform tasks collectively through automated chat.
BOAResponde
BOAResponde: Chatbot para consultas del Boletín Oficial de Argentina. Ofrece respuestas rápidas y precisas sobre normativas y decretos. Actualización diaria, interfaz intuitiva y tecnología IA para procesamiento en lenguaje natural.
crypto-market-prophet-prediction-api
This FastAPI-based API serves as the backend for the Crypto Market Prediction App, utilizing the Prophet forecasting model to deliver accurate cryptocurrency price predictions. It provides robust endpoints for fetching historical data and generating predictions, facilitating seamless integration with front-end applications.
DjangoTurorialAdvanced
Django Essentials: Step-by-Step Learning
instagram-bot
This repository hosts the Instagram Artistic Bot, a tool leveraging generative AI for creating and posting cyberpunk-style art on Instagram. It automatically generates images, captions, and hashtags, and publishes them, aiming to simplify content creation for artists and social media enthusiasts. For detailed inform
MedicalRecordsManagement
MedicalRecordsManagement: A Flask + dynamic front-end platform for efficient patient data handling with NLP and real-time streaming
rag_with_knowledge_graphs
This repository contains a Jupyter notebook, which is designed to demonstrate the process of building knowledge graphs using advanced natural language processing and machine learning techniques.
scraper_boletin_oficial
Este proyecto utiliza Python y BeautifulSoup para realizar web scraping en la página del Boletín Oficial de Argentina. Extrae datos relevantes como fechas de publicación, títulos de normativas, enlaces y textos de las normas, almacenándolos en un DataFrame.
twitter_bot
Este repositorio contiene el código para un Bot de Tweets de Noticias, diseñado para scrapear automáticamente, resumir y tuitear artículos de noticias argentinas de diversas fuentes.
tommanzur's Repositories
tommanzur/ArguBot
ArguBot is a chatbot based on the doctoral thesis "Construction of Arguments and Socio-Technical Controversies" by Tomás Manzur. It offers interactive access to the thesis's insights on the Plan Provincial de Ordenamiento Territorial of Mendoza.
tommanzur/scraper_boletin_oficial
Este proyecto utiliza Python y BeautifulSoup para realizar web scraping en la página del Boletín Oficial de Argentina. Extrae datos relevantes como fechas de publicación, títulos de normativas, enlaces y textos de las normas, almacenándolos en un DataFrame.
tommanzur/autogen_groupchat_RAG
This project demonstrates a group chat system powered by Retrieval Augmented Generation (RAG), utilizing the `autogen` library. It showcases how conversational agents, powered by llms, tools, or human inputs, can perform tasks collectively through automated chat.
tommanzur/DjangoTurorialAdvanced
Django Essentials: Step-by-Step Learning
tommanzur/rag_with_knowledge_graphs
This repository contains a Jupyter notebook, which is designed to demonstrate the process of building knowledge graphs using advanced natural language processing and machine learning techniques.
tommanzur/Airbnb-Income-Analysis
Airbnb-Income-Analysis es un proyecto que utiliza Jupyter Notebook para analizar y reportar los ingresos de propiedades alquiladas en Airbnb. Incluye conversión de moneda, visualizaciones de ingresos y generación de informes HTML, basado en datos CSV de Airbnb.
tommanzur/AMEX_default_prediction
This repository focus on predicting credit card defaults for American Express customers. The main tools used in this project are likely to be data analysis and machine learning techniques https://www.kaggle.com/competitions/amex-default-prediction
tommanzur/autogen_airbnb_assistant
This project demonstrates the integration of an automated agent system using the autogen library to perform specific web scraping tasks.
tommanzur/BOAResponde
BOAResponde: Chatbot para consultas del Boletín Oficial de Argentina. Ofrece respuestas rápidas y precisas sobre normativas y decretos. Actualización diaria, interfaz intuitiva y tecnología IA para procesamiento en lenguaje natural.
tommanzur/chat-bot-gemini
Built using JavaScript and integrating Google's Generative AI, ChatBot is a modern chat application that showcases cutting-edge technology in natural language processing and user interaction.
tommanzur/chatbot
This project is a web application that uses the OpenAI API to create an interactive chatbot that can answer the questions and comments of the users. The chatbot is based on the GPT-3 language model, which is capable of generating coherent and creative responses from a large amount of data.
tommanzur/crypto-market-prophet-prediction-api
This FastAPI-based API serves as the backend for the Crypto Market Prediction App, utilizing the Prophet forecasting model to deliver accurate cryptocurrency price predictions. It provides robust endpoints for fetching historical data and generating predictions, facilitating seamless integration with front-end applications.
tommanzur/instagram-bot
This repository hosts the Instagram Artistic Bot, a tool leveraging generative AI for creating and posting cyberpunk-style art on Instagram. It automatically generates images, captions, and hashtags, and publishes them, aiming to simplify content creation for artists and social media enthusiasts. For detailed inform
tommanzur/MedicalRecordsManagement
MedicalRecordsManagement: A Flask + dynamic front-end platform for efficient patient data handling with NLP and real-time streaming
tommanzur/pytetris
Testris game developed with pygame
tommanzur/twitter_bot
Este repositorio contiene el código para un Bot de Tweets de Noticias, diseñado para scrapear automáticamente, resumir y tuitear artículos de noticias argentinas de diversas fuentes.
tommanzur/GlobantDataEngineeringCodingChallenge
This repository contains the solution for Globant's Data Engineering Challenge. The project implements an API using FastAPI, SQLAlchemy, and PostgreSQL, managed within a Conda environment. The API allows for CRUD operations on the database and is accompanied by unit tests to ensure its proper functionality.
tommanzur/langchain_sentimen_analysis
The project showcases two main approaches: a baseline model using RandomForest for initial sentiment classification and an enhanced analysis leveraging LangChain to utilize Large Language Models (LLMs) for more in-depth sentiment analysi
tommanzur/solar_syste_symulator
This repository contains the code for a solar energy system simulator designed to model the performance of a residential solar power setup. The simulator takes into account various factors such as solar efficiency, home power consumption, battery charge and discharge cycles, and grid interactions.
tommanzur/stock-market-prophet-forecasting
Stock Market Prophet Forecasting is a Python-based repository utilizing the Prophet forecasting library to predict stock market trends. This project aims to provide accurate, automated predictions to aid investors in making informed decisions. It features data preprocessing, model training, and visualization tools
tommanzur/trading_bot
Implementation of an automated trading strategy that leverages machine learning and sentiment analysis to make informed trading decisions based on market news. The strategy utilizes the FinBERT model for sentiment analysis and interacts with the Alpaca API for trading actions.
tommanzur/virtual_assistant
This GitHub repo features a virtual assistant using OpenAI's GPT-3.5-Turbo-0613, designed for Spanish speech-to-speech interaction. It efficiently handles tasks through OpenAI API function calls, offering a seamless, conversational user experience.