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Showing 5 open source projects for "java open source"
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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.
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sequoia-dap
SEQUOIA ocean data assimilation platform (a SIROCCO suite tool)
Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite elements), multi-algebra (plug-in analysis kernels), multi-model (simple standardized interface). The program supports reduced-order data assimilation methods, as well as Ensemble assimilation approaches such as the Ensemble Kalman Filter. Recent additions... -
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statTools
Command-line tools for simple statistics
statTools contains command-line tools for simple statistics -
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GADfit
Global nonlinear optimization with automatic differentiation
NOTE: Development continued at GitHub! Current version is higher than 1.2.0. GADfit is a Fortran implementation of global nonlinear curve fitting, based on a modified Levenberg-Marquardt algorithm. Global fitting refers to fitting many datasets simultaneously with some parameters shared among the datasets. The fitting procedure is very fast and accurate thanks to the use of automatic differentiation. The model curves (fitting functions) can be of essentially arbitrary complexity. This... -
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Implementation in Python of some of the statistical methods provided by "asurv", the survival analysis software.
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Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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This is the Linux porting of the New Seats Tramo. Developed by Gianluca Caporello. Create a new TSW (XWIN) called TS-XWin using the Lazarus IDE. A C++ Interface has been created and with the SWIG package the idea is to create a Java interface.
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