Stars
Natural Gradient Boosting for Probabilistic Prediction
Jupyter extensions that help you write code faster: Context aware AI Chat, Autocomplete, and Spreadsheet
Bayesian learning and inference for state space models
Code that I show on my YouTube Channel
Rapid fuzzy string matching in Python using various string metrics
Turn (almost) any Python command line program into a full GUI application with one line
GPU-accelerated Factors analysis library and Backtester
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A lightweight LLVM python binding for writing JIT compilers
A library to model multivariate data using copulas.
NumPy aware dynamic Python compiler using LLVM
Additional linear models including instrumental variable and panel data models that are missing from statsmodels.
A game theoretic approach to explain the output of any machine learning model.
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
High-performance TensorFlow library for quantitative finance.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Automatic extraction of relevant features from time series:
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
STUMPY is a powerful and scalable Python library for modern time series analysis
Probabilistic time series modeling in Python
Statsmodels: statistical modeling and econometrics in Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoo…