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Accelerate Deep Learning on Raspberry Pi


 
 Accelerate Deep Learning on Raspberry Pi

Accelerate Deep Learning on Raspberry Pi | Udemy Coupon ED

How to Accelerate your AI Object Detection Models 5X faster on a Raspberry Pi 3, using Intel Movidius for Deep Learning Get Udemy Course

What you'll learn
  • Learn how to get Started with Raspberry Pi from Scratch
  • Discover various Object Detection models
  • Introduction to Deep Learning and Tensorflow lite
Requirements
  • Raspberry Pi 3, Power Supply and Case
  • Intel Movidius Neural Compute Stick
  • SD Card Class 10 (UHS class 1 or 3)
  • Webcam
  • Prior Raspberry Pi or Deep Learning Knowledge (Not required but helpful)
 Description

Learn how we implemented Deep Learning Object Detection Models on Raspberry Pi and accelerated them with Intel Movidius Neural Compute Stick.
When we first got started in Deep Learning particularly in Computer Vision, we were really excited at the possibilities of this technology to help people. The only problem is, that image classification and object detection runs just fine on our expensive, power consuming and bulky Deep Learning machines. However, not everyone can afford or implement AI for their practical applications.
This is when we went searching for an affordable, compact, less power hungry alternative. Generally if we'd want to shrink our IoT and automation projects, we'd often look to the Raspberry Pi which is versatile computing solution for numerous problems. This made us ponder about how we can port out deep learning models to this compact computing unit. Not only that, but how could we run it at close to real-time?
Amongst the possible solutions we arrived at using the raspberry pi in conjunction with an AI Accelerator USB stick that was made by Intel to boost our object detection frame-rate. However it was not so simple to get it up and running. Implementing the documentation, we landed up with a series of bugs after bugs, which became a bit tedious.
After endless posts on forums, tutorials and blogs, we have documented a seamless guide in the form of this course; which will show you, step-by-step, on how to implement your own Deep Learning Object Detection models on video and webcam without all the wasteful debugging. So essentially, we've structured this training to reduce debugging, speed up your time to market and get you results sooner.

In this course, here's some of the things that you will learn:
  • Getting Started with Raspberry Pi even if you are a beginner,
  • Deep Learning Basics,
  • Object Detection Models - Pros and Cons of each CNN,
  • Setup and Install Movidius Neural Compute Stick (NCS) SDK,
    Currently, the OpenVINO is available for Raspbian, so the NCS2 is already compatible with the Raspberry Pi, but this course is mainly for the Movidius (NCS version 1).
  • Run Yolo and Mobilenet SSD object detection models in recorded or live video
You also get helpful bonuses:

*OpenCV CPU inference
*Introduction to Custom Model Training

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