Iml Libraries

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Iml Libraries

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data. Once TPOT is finished searching (or you get…

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations…

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Note that when running the tutorials, the packages are not automatically added. Thus you will need to add the packages manually or use the internal Project/Manifest tomls to instantiate the correct p…

interpretable_machine_learning_with_python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Examples of techniques for training interpretable machine learning (ML) models, explaining ML models, and debugging ML models for accuracy, discrimination, and security. The notebooks highlight techn…

Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization

directly in Python. To install diffeqpy, use pip: and you're good! We can plot the solution values using matplotlib: We can utilize the interpolation to get a finer solution: or we can draw the phase…

H2O.ai Machine Learning Interpretability Resources

Machine learning algorithms create potentially more accurate models than linear models, but any increase in accuracy over more traditional, better-understood, and more easily explainable techniques i…

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: The SciML Bench suite is made to be a comprehens…

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TPOT stands for Tree-based Pipeline Optimization Tool. TPOT2 is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. Consider TPOT2 your Data …