Search Results for "genetic algorithm scheduling python"
Sort By:
Showing 16 open source projects for "genetic algorithm scheduling python"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Keep company data safe with Chrome EnterpriseMake AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
-
1
PyGAD
Source code of PyGAD, Python 3 library for building genetic algorithms
PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function. -
2
Appfl
Advanced Privacy-Preserving Federated Learning framework
APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups. -
3
Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
4
This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.
-
Inventors: Validate Your Idea, Protect It and Gain Market AdvantagessenseIP is an AI innovation platform for inventors, automating any aspect of IP from the moment you have an idea. You can have it researched for uniqueness and protected; quickly and effortlessly, without expensive attorneys. Built for business success while securing your competitive edge.
-
5
Evolving Objects
This project have been merged within Paradiseo.
See the new project page: https://nojhan.github.io/paradiseo/ (Archived project page: http://eodev.sourceforge.net/) -
6
This project is a complete cross-platform (Windows, Linux) framework for Evolutionary Computation in pure python. See the project site at http://pyevolve.sourceforge.net or the blog at http://pyevolve.sourceforge.net/wordpress
-
7
A genetic algorithm in Python for evolving programs that write a given string to an allocated dataspace, using a made-up machine language with only 7 instructions and flow reversal.
-
8
Based on the introduction of Genetic Algorithms in the excellent book "Collective Intelligence" I have put together some python classes to extend the original concepts.
-
9
Springbots is a python application which takes a set of 2d physical structures built with nodes and movable springs and evolve them for specific tasks like walking, swimming and jumping using genetic algorithm.
-
Cloud data warehouse to power your data-driven innovationBigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
-
10
-
11
The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
-
12
DrPangloss is a python implementation of a three operator genetic algorithm, complete with a java swing GUI for running the GA and visualising performance, generation by generation
-
13
GACS (Genetic Algorithm Class Scheduler) aims to provide to academic institutions an efficient and automatic way to generate their time scheduling for the classes that will be imparted in an academic period.
-
14
Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The
-
15
TA scheduler based on a genetic algorithm to make the tedious task of scheduling TA's more efficient.
-
16
aVolve is an evolutionary/genetic algorithm designed to evolve single-cell organisms in a micro ecosystem. It currently uses the JGAP Genetic algorithm, but does include a primitive genetic algorithm written in Python.
- Previous
- You're on page 1
- Next
