Training and validating the Moku Neural Network with Python (Part 2)
Are you looking to unlock the power of FPGA-based neural networks for fast, flexible signal analysis? In this video, Liquid Instruments engineer Jason Ball, Ph.D., shows you how to build, train, and validate a neural network using Python, and export the information for use on a Moku device. This is part two of a three-part series on training and deploying a neural network with Moku.
Find out how the Moku Neural Network can accelerate your research:
https://liquidinstruments.com/neural-...
For prerequisites and further instructions, see the following page:
https://liquidinstruments.com/blog/cr...
For an interactive demonstration, speak to an applications engineer:
https://www.liquidinstruments.com/req...
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