danielseussler
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⚡ A Fast, Extensible Progress Bar for Python and CLI
An educational resource to help anyone learn deep reinforcement learning.
Bayesian Modeling and Probabilistic Programming in Python
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
Uplift modeling and causal inference with machine learning algorithms
Missing data visualization module for Python.
A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
A curated list of awesome Dash (plotly) resources
Natural Gradient Boosting for Probabilistic Prediction
Extensible, parallel implementations of t-SNE
Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
A Python package for causal inference in quasi-experimental settings
BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.
A python package that extends Google Earth Engine.
Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax
Python library for CMA Evolution Strategy.
Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/
scikit-learn compatible implementation of stability selection.
Fast High-Dimensional Fixed Effects Regression in Python following fixest-syntax
CmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to compile a Stan program and fit the model to data using CmdStan.
A Python 3 gradient-free optimization library
Exploring and eliciting probability distributions
Gapminder's fact-base with local & global statistics
Minimal Implementation of Bayesian Optimization in JAX