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Miguel Ávila 's Projects

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Primer repositorio para aprender

awesome-quant icon awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

dalle2-pytorch icon dalle2-pytorch

Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch

dsge-utilities icon dsge-utilities

Python Programming Code for Dynamic Stochastic General Equilibrium Modeling

fes icon fes

Code and Resources for "Feature Engineering and Selection: A Practical Approach for Predictive Models" by Kuhn and Johnson

fingpt icon fingpt

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

metaapi-python-sdk icon metaapi-python-sdk

Python SDK for MetaApi, a professional cloud forex trading API for MetaTrader platform which supports both MetaTrader MetaTrader 5 and MetaTrader 4. CopyFactory copy trading API included. Free usage tier available.

oandapybot icon oandapybot

Simple python bot for trading forex on oanda.com

phd_economics icon phd_economics

Codes and other files related to my work pursuing a Ph.D. in Economics at Universidade Federal do Rio Grande do Sul (UFRGS) - 2017/2021

projects icon projects

A collection of all the projects built on TheCodex.Me

pyspice icon pyspice

Simulate electronic circuit using Python and the Ngspice / Xyce simulators

python-trading-robot icon python-trading-robot

A trading robot, that can submit basic orders in an automated fashion using the TD API.

recursos-datos icon recursos-datos

Recopilación de recursos de ciencias de datos por parte de la comunidad Datos Para Todos

rl-baselines3-zoo icon rl-baselines3-zoo

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

rl-tutorial-jnrr19 icon rl-tutorial-jnrr19

Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

rliable icon rliable

[NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.

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