Search Results for "machine learning platform"
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Showing 6 open source projects for "machine learning platform"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Build Agents and Models on One PlatformGemini 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.
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PRMLT
Matlab code of machine learning algorithms in book PRML
This Matlab package implements machine learning algorithms described in the great textbook: Pattern Recognition and Machine Learning by C. Bishop (PRML). It is written purely in Matlab language. It is self-contained. There is no external dependency. This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). -
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Octave
my octave exercises for 2011 stanford machine learning class
This repository is a personal archive of Octave exercises and assignments for the 2011 Stanford Machine Learning class. The author uses the Octave programming environment (which is similar to MATLAB) to implement the homework assignments (ex1 through ex7), providing code solutions, cheat sheets, and scratch files. Octave / MATLAB code illustrating algorithms taught in the class. Cheat sheet for Octave / MATLAB commands. Readme and licensing information. -
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Overhead Imagery Research Data Set (OIRDS) - an annotated data library & tools to aid in the development of computer vision algorithms
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The project goal is to develop several IP cores that would implement artificial neural networks using FPGA resources. These cores will be designed in such a way to allow easy integration in the Xilinx EDK framework.
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