waith's repositories
Data-Science-EBooks
This repository contains resources in the form of ebooks, which are related to Data Science, Machine Learning, and similar topics.
options-2-trees
Interactive visualization of the CRR binomial options pricing model
nempy
A Python package for modelling the Australian National Electricity Market dispatch procedure
pykan
Kolmogorov Arnold Networks
perpetual
A self-generalizing, hyperparameter-free gradient boosting machine
time-series-analysis
Collection of notebooks for time series analysis
mlx-examples
Examples in the MLX framework
gluonts
Probabilistic time series modeling in Python
moment
MOMENT: A Family of Open Time-series Foundation Models
causal_ai
This project introduces Causal AI and how it can drive business value.
PefCodeBench
Codebase to reproduce probabilistic forecasting experiments
efficient-kan
An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).
imodelsX
Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.
energy-py-linear
Optimize energy assets using mixed-integer linear programming
deep-learning-for-finance
The Official Repository of Deep Learning for Finance
conformal-prediction
Lightweight, useful implementation of conformal prediction on real data.
Conformal-Prediction-MAPIE-Algotrading101
Conformal Prediction - A Practical Guide with MAPIE
Machine-Learning-Engineering-for-Production
A repository for the Machine Learning Engineering for Production Specialization provided by Deeplearning.ai .
rlfinance
The code used for the free quants@dev Webinar series on Reinforcement Learning in Finance
adsfcr
Applied Data Science for Credit Risk
mcrps
Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices: Data and Code
conformal-predictions-from-scratch
Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.
mlforecast
Scalable machine 🤖 learning for time series forecasting.
cyclic-boosting
implementation of Cyclic Boosting machine learning algorithms
DistrNNEnergy.jl
Barunik, Jozef and Hanus, Luboš, Learning Probability Distributions of Day-Ahead Electricity Prices
energy-py
Reinforcement learning for energy systems