PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants. https://pypop.rtfd.io/
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Updated
May 29, 2024 - Python
PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants. https://pypop.rtfd.io/
The first open-source AI-driven tool for automatically generating system-level test cases (also known as fuzzing) for web/enterprise applications. Currently targeting whitebox and blackbox testing of Web APIs, like REST, GraphQL and RPC (e.g., gRPC and Thrift).
Common machine learning algorithm implementations
This repositories include the IEEE Congress on Evolutionary Computation Benchmark functions suite (IEEE CEC 2014 2017 2020 2022). You can use the untitled.m to form a figure of the benchmark function.
Evolutionary multi-objective optimization platform
Python library for evolutionary and swarm intelligence algorithms.
(GECCO2023 Best Paper Nomination) CMA-ES with Learning Rate Adaptation
Example programs for usage of the Chips-n-Salsa library
Open Funsearch implementation of Google Deepmind's Funsearch
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Automated modeling and machine learning framework FEDOT
A (still growing) paper list of Evolutionary Computation (EC) published in some (rather all) top-tier (and also EC-focused) journals and conferences. For EC-focused publications, only Parallel/Distributed EC are covered in the current version.
Python framework for automated time series classification and regression
🧬 Search-Based approach to repair unrealisable Linear-Time Temporal Logic (LTL) specifications.
An interactive real-time simulation for evolving multicellular organisms.
An evolutionary algorithm library in C++
Evolutionary Algorithms Framework
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
This course covers the applied side of algorithmics in machine learning and deep learning, focusing on hands-on coding experience in Python.
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