madquirk-hash's repositories
3w_dataset
The first realistic and public dataset with rare undesirable real events in oil wells.
AI-CAPS
The is a Streamlit webapp that allows user to speech to text in 18 Languages.
AutoDL
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
bayesian-variable-selection-1
Report made for the MSc course in Bayesian Statistics at Bocconi University
Causal-Recommender-Systems
An index of causal inference based recommendation algorithms.
Deep-Learning-Machine-Learning-Stock
Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.
Deep-Portfolio-Management-Reinforcement-Learning
This repository presents our work during a project realized in the context of the IEOR 8100 RL Class at Columbia University.
EliteQuant
A list of online resources for quantitative modeling, trading, portfolio management
Extreme-Events-extraction
Using python to extract (extreme) events from time series
FeatBoost
Boosted Iterative Input Selection
fuzzyftapy
Thesis work on Fuzzy Fault Tree Analysis
Group-wise-Reinforcement-Feature-Generation-for-Optimal-and-Explainable-Representation-Space-Reconst
code for SIGKDD 2022 paper : Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction
Intelligent-Quantitative-Trading
Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio management and optimization.
intelligent-trading-bot
Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
LightAutoML
LAMA - automatic model creation framework
LSTM-MultiStep-Forecasting
Implementation of Electric Load Forecasting Based on LSTM (BiLSTM). Including direct-multi-output forecasting, single-step-scrolling forecasting, multi-model-single-step forecasting, multi-model-scrolling forecasting, and seq2seq forecasting.
mead-baseline
Deep-Learning Model Exploration and Development for NLP
PIML
The official PyTorch implementation of "Physics-infused Machine Learning for Crowd Simulation" (KDD'22)
prince
:crown: Python factor analysis library (PCA, CA, MCA, MFA, FAMD)
RBAA
Regime Based Asset Allocation with MPT, Random Forest and Bayesian Inference
SHRA
This reposity presents scenario hurricane risk analysis
SIGIR21-SURGE
Official implementation of SIGIR'2021 paper: "Sequential Recommendation with Graph Neural Networks".
SPLConqueror
SPL Conqueror is a library to learn the influence of configuration options of configurable software systems on non-functional properties.
ssqueezepy
Synchrosqueezing, wavelet transforms, and time-frequency analysis in Python
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
TFT_darts
probabilistic forecasting with Temporal Fusion Transformer