Boltzmann Machines in TensorFlow with examples
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Updated
Nov 5, 2021 - Jupyter Notebook
Boltzmann Machines in TensorFlow with examples
Parallel Hyperparameter Tuning in Python
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
Python bindings and scikit-learn interface for the Operon library for symbolic regression.
Contains data preprocessing and visualization methods for ADL datasets.
A simple template of a Python API (web-service) for real-time Machine Learning predictions, using scikitlearn-like models, Flask and Docker.
A scikit-learn-compatible module for Isolation-based anomaly detection using nearest-neighbor ensembles
Machine Learning Transition State Analysis (MLTSA) suite with Analytical models to create data on demand and test the approach on different types of data and ML models.
Optimizers for/and sklearn compatible Machine Learning models
Polynomial regression and classification with sklearn and tensorflow
Scikit learn compatible constrained and robust polynomial regression in Python
ParALleL frAmework for moDel selectIOn
Bleeding Edge machine learning algorithms
combination of EvalML with Rapids for the WiDS 2021 competition
A tool for performing cross-validation with panel data
Time series features creation
thermometer encoding with sklearn interface
Wrapper which provides scikit-learn-compatible implementation of SkNN sequence labeling algorithm
SVR for multidimensional labels
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