Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.
Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
Try It Free
Train ML Models With SQL You Already Know
BigQuery automates data prep, analysis, and predictions with built-in AI assistance.
Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
RL++ is an easy to use modular open source library for Reinforcement Learning written in C++. It includes learning algorithms (TD, Sarsa, Q) as well as the implementation of value function representations (LookupTable, TileCoding, Neuronal Network).
The Parameter Tuning Unity (PTU) aims to adapt the parameters of ever connected multi-agents system, or expert system with a plugged optimization heuristic likes the descent of gradient for instance.
It moves by itself inside networks like virus infection & plagues, it is being written to solve computer virus problem drastically and responsibly. It is legal, free and open for public domain to improve W3 ICT Security.
This is a cross-platform framework for using Genetic Algorithms for solutions. Written in Java and uses convinient plug-in features for every phase in the genetic development, while maintaining an easy-to-use API for easy integration into applications.
Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.
Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
This project aim to provide a crowd movement simulation based on primitive human behaviours and emerging behaviours for research and educational purposes. The application (front-end) is generic and can be reused.
It's an implementation of the A* algorithm together with a grid processor which pre-processes 8-bit bpm graphic files using a variable resolution and an SDL user interface to test it.
Procedural content generation of deterministic and complex entities, with properties and other entities inside, defined by an editable XML file, along with a framework to simulate actions, compositions, and interactions of entities.
Secure by design, portable by default. Recover clean, fast, anywhere. Start a free trial.
Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.
This projects implements various optimization heuristics and meta-heuristics (such as local search, VND, GRASP, Simulated Annealing, and more still to come) finding solutions on the post enrolment course timetabling problem.
Generic engine to filter information.
We wish to show that the power of expression of a filter makes it possible to appreciably reduce the size of the code necessary to extract information and that it is possible in Python.
JavaGO is an Open Source Java library for the Game of GO (weiqi, baduk) analysis. Implements: base game classes, montecarlo simulations, SGF reader/writer, game variants, GTP, etc. Elegant interfaces/class design. Speed efficient w/small footprint. TDD.