Technical Document "Deep Learning Using FPGA" *Currently Available for Free
Key points on tools for starting the design and implementation of machine learning-based applications!
Deep learning algorithms are gaining popularity in IoT applications at the edge due to their human-level accuracy in object recognition and classification. As a subset of machine learning, deep learning algorithms are inspired by the neural networks of the human brain, and by extending the concept of biological neural networks into machine learning, they effectively solve learning problems that were previously impossible. This document provides a detailed introduction to how Deep Neural Networks (DNN) operate and why FPGAs are becoming popular for DNN inference. Additionally, it includes the tools necessary to design and implement deep learning-based applications using FPGAs on Aldec's TySOM-3A-ZU19EG embedded development board, which features the largest FPGA from the Xilinx Zynq Ultrascale+ MPSoC family. We encourage you to make use of this information. *For more details, please refer to the PDF document or feel free to contact us.*
- Company：アルデック・ジャパン
- Price：Other
