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Build Securely on Azure with Proven Frameworks
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neuralnetgen is intended to be a universal neuralnet generator that receives a neuralnet description (on NeuralNet Description Language, also developed on this project) and generates ANSI C code of a library that implements it.
Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.
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.
ptsa (pronounced pizza) is a Python module for performing time series analysis. Although it is specifically designed with neural data in mind (EEG, MEG, fMRI, etc...), the code should be applicable to almost any type of time series.
mozg is a flexible, fast neurolibrary. It allows one to create, learn and use multi-layer perceptron (MLP), which is the most popular artificial neural network (ANN). This work is based on library originally written by Alexy Filin.