There are 3 repositories under deap topic.
Feature Selection using Genetic Algorithm (DEAP Framework)
ML hyperparameters tuning and features selection, using evolutionary algorithms.
CNN architecture exploration using Genetic Algorithm
codegen from expression to others, such as polars, pandas
A Python implementation of the decomposition based multi-objective evolutionary algorithm (MOEA/D)
Emotional Video to Audio Transformation with ANFIS-DeepRNN (Vanilla RNN and LSTM-DeepRNN) [MPE 2020]
A project on improving Neural Networks performance by using Genetic Algorithms.
Kaggle LANL Earthquake Prediction challenge, Genetic Algorithm (DEAP) + CatboostRegressor, private score 2.425 (31 place)
A stochastic circuit optimizer for Cadence Virtuoso, using the NSGA-II genetic algorithm.
Genetic algorithm to solve modular exams scheduling problem written in Python.
[ICASSP 2022] EEG - Music Cross Modal Learning
Evolutionary Composition uses genetic algorithms to create and enhance musical melodies.
Code for my Master's Thesis at the Institute of Medical Informatics, Universität zu Lübeck.
Motif discovery for DNA sequences using multiobjective optimization and genetic programming.
Playing around with DEAP's genetic programming to generate a regex that matches everything in one list and nothing in another list
( 🦉 ) This code lab intended to introduce new Machine Learning Algorithm // DEAP : Distributed Evolutionary Algorithm Framework.
Evolutionary algorithm for neural network structure
Seminar project at FER led by Assistant Professor Marko Čupić
Symbolic regression of physical models via Genetic Programming.
Playing the (in)famous Flappy Bird game using NEAT and Differential Evolution.
Thesis activity carried out during the laboratory internship at the University of Parma, the goal is to generate filters for denoise and edge detection using genetic programming.
This repository helps creating a docker container with lots of evolutionary algorithms packages in python
Proof of concept about DEAP in Python in order to solve TSP
Genetic Algorithm as an approach to select image restoration parameters that provides the greatest improvement to a turbid underwater image.
EPTune: Parameter Tuning using Evolutionary Algorithm.