Start building on Google Cloud with $300 in free credits. No commitment, no credit card required until you're ready to scale.
Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
Start Free Trial
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.
LibVsg is a 2D/3D software library with a focus on basic geometric manipulations. It's released under the GNU LGPL. Written for C, it provides support for single and double precision arithmetics. A Python wrapper also comes with the distribution.
Porcupine is an open-source Python based web application server that provides front-end and back-end revolutionary technologies for building modern data-centric Web 2.0 applications.
The main intention of this project is to support the SNNS (Stuttgart Neural Net Simulator) with patches, bugfixes, tools and add on developments. Second target is to publish useful links and information about the SNNS.
Kreatrix is dynamic prototype based object orientated language. It has been inspirated by Io and Self. The syntax is similar to Smalltalk. It has small VM with modules (like Python). Some modules bind external library, for example: GTK+ and SDL.
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.
Pink is an image processing library developed at ESIEE Engineering for research and teaching purposes. It contains implementations of over 200 algorithms for image segmentation and filtering.
The intention of this project is to give all serious users of the SNNS a place where they find a bugfix and patch management and where they get useful information about the SNNS.
This is a c-library that provides tools for advanced
analysis of electrophysiological data. It features
denoising, unsupervised classification, time-frequency
analysis, phase-space analysis, neural networks, time-warping and
more.
Metaboflux is a generic approach for predicting flux distribution in metabolic networks under multiple and various constraints deducted from the experiments, to increase the biological relevance of the model.
The eTeachingKit project aims to provide software and teaching material for offering an open e-course. Find an e-learning application for the student, a management application for the teacher and various teaching material for programming in C.
pyxser stands for python xml serialization and is a python object to XML serializer that validates every XML deserialization against the pyxser 1.0 XML Schema. pyxser is written entirely in C as a python extension.
The SIMP/STEP platform provides a fast, efficient, portable abstract framework for interactive and scripted cellular automata and lattice gas computing in the Python environment. SIMP provides a high-level 'programmable matter' laboratory built on
Cca-forum unifies the Common Component Architecture tools and tutorial. It includes the CCA specifications, the Ccaffeine framework for HPC, and related tools. These support multilanguage scientific and parallel computing.
PythonCGNS is a simple python language binding for the CGNS library, created with the SWIG utility. For more advanced python mappings have a look at the pyCGNS project. It provides methods for reading, writing and manipulation of cgns files.
This is a lightweight and fast library for reading and writing any PNM file - PBM, PGM and PPM, up to 16 bits per sample, in ascii/binary format. Library contains also a Python bindings - module pixfiles with PixFile class.
This is a python implementation that handles floating points correctly,there are still some bugs but I'm working on it . The point was to work around some stuff that made no sense for floats,like 0.1+0.2 == 0.3 is false.