Pinned Repositories
aiif
Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O'Reilly) by Yves Hilpisch.
catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Colab_studies
All Colab studies
defaultproject
Web Application bootstrap for Go
drl-portfolio-management
CSCI 599 deep learning and its applications final project
FinRL-Meta
FinRL-Meta: Dynamic datasets and market environments for FinRL.
FinRL-Trading
For trading. Please star.
five-minute-midas
Predicting Profitable Day Trading Positions using Decision Tree Classifiers. scikit-learn | Flask | SQLite3 | pandas | MLflow | Heroku | Streamlit
github-feed-clone-ui
github_app_open_source
andrefagundes10's Repositories
andrefagundes10/aiif
Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O'Reilly) by Yves Hilpisch.
andrefagundes10/catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
andrefagundes10/FinRL-Meta
FinRL-Meta: Dynamic datasets and market environments for FinRL.
andrefagundes10/FinRL-Trading
For trading. Please star.
andrefagundes10/five-minute-midas
Predicting Profitable Day Trading Positions using Decision Tree Classifiers. scikit-learn | Flask | SQLite3 | pandas | MLflow | Heroku | Streamlit
andrefagundes10/github-feed-clone-ui
andrefagundes10/github_app_open_source
andrefagundes10/hftbacktest
A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.
andrefagundes10/How-to-Guess-Accurately-3-Lottery-Numbers-Out-of-6-using-LSTM
How to Guess Accurately 3 Lottery Numbers Out of 6
andrefagundes10/ifood-site-clone
andrefagundes10/LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
andrefagundes10/llm4regression
Examining how large language models (LLMs) perform across various synthetic regression tasks when given (input, output) examples in their context, without any parameter update
andrefagundes10/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
andrefagundes10/machine_learning_examples
A collection of machine learning examples and tutorials.
andrefagundes10/medium
andrefagundes10/MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
andrefagundes10/MetaTraderForecast
RNN based Forecasting App for Meta Trader and similar trading platforms
andrefagundes10/Project-1-Closing-Price-Stock-Regressor-Version-1.0
Predicting a stock's daily closing price using automated multiple linear regression.
andrefagundes10/rlfinance
The code used for the free quants@dev Webinar series on Reinforcement Learning in Finance
andrefagundes10/RLTrader
A cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym
andrefagundes10/rust-api
andrefagundes10/scikit-learn
scikit-learn: machine learning in Python
andrefagundes10/siml
Machine Learning algorithms implemented from scratch
andrefagundes10/sktime
A unified framework for machine learning with time series
andrefagundes10/social-app-prototype
💻 an app made with react native to prototype a social app
andrefagundes10/StockForecast
Using machine learning to predict/forecast the future trend of stock prices.
andrefagundes10/tensorflow-deep-learning
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
andrefagundes10/TimeSeriesPrediction
Time Series Prediction
andrefagundes10/tsai
Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
andrefagundes10/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow