PYNQ FPGA Development with Python Programming & VIVADO

Last updated 9/2021
Created by Digitronix Nepal
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 22 Lectures ( 3h 49m ) | Size: 1.86 GB

Learn Python Development with PYNQ FPGA: covers from Image Processing to Acceleration of Face Recognition Projects.

What you'll learn
PYNQ Development Flow
Implementing Face Recognition with PYNQ FPGA
Image and Video Processing with PYNQ FPGA and Python Library
Creating Custom Overlay for PYNQ on VIVADO
Machine Learning Algorithm Implementation on PYNQ
Installing Tensorflow on PYNQ and Implementing Neural Network on PYNQ
Python Programming with Jupyter Interface on Internet Browser

Requirements
FPGA Design Basics
Basic of Python Programming
PYNQ FPGA Board
Eager to Learn Pynq Development with Python and VIVADO

Description
PYNQ (Python+Zynq), An FPGA development platform from Xilinx is an Open Source FPGA development platform. This Course covers from the Architecture of PYNQ (Zynq 7000), PYNQ Development Flow, Basic GPIO interfacing with PYNQ FPGA, Image Processing with PYNQ, using PYNQ libraries as sci_pi, OpenCV, Installing Tensorflow on PYNQ,Machine Learning with Pynq, Neural Network Implementation on PYNQ, Creating Custom PYNQ Overlay on Xilinx VIVADO . After completing this course you will also know about the Acceleration methodology on the PYNQ Development Platform. Another important section of this course is Implementation of Machine Learning Algorithms on Python for Image Processing and other projects. We will implement Artificial Neural Networks (ANN) algorithms as CNN, BNN and other Neural Networks for real time projects as Number Plate Recognition, Face Recognition etc. At the another section we will have sessions on "How to design Overlay system with VIVADO for PYNQ FPGA". This session is based on the VIVADO HLS & IP integrator for creating custom Overlay. 

Who this course is for
Electrical Engineering
Computer Science
Hardware Design Enthusiast

Buy Premium Account From My Download Links & Get Fastest Speed.