Accelerate Deep Learning on Raspberry Pi

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About This Course

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

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

Personal help within the course

I donate my time to regularly hold office hours with students. During the office hours you can ask me any business question you want, and I will do my best to help you. The office hours are free. I don't try to sell anything.

Students can start discussions and message me with private questions. I answer 99% of questions within 24 hours. I love helping students who take my courses and I look forward to helping you. 

I regularly update this course to reflect the current marketing landscape.

Get a Career Boost with a Certificate of Completion  

Upon completing 100% of this course, you will be emailed a certificate of completion. You can show it as proof of your expertise and that you have completed a certain number of hours of instruction.

If you want to get a marketing job or freelancing clients, a certificate from this course can help you appear as a stronger candidate for Artificial Intelligence jobs.

Money-Back Guarantee

The course comes with an unconditional, Udemy-backed, 30-day money-back guarantee. This is not just a guarantee, it's my personal promise to you that I will go out of my way to help you succeed just like I've done for thousands of my other students. 

Let me help you get fast results.  Enroll now, by clicking the button and let us show you how to develop Accelerated AI on Raspberry Pi.

  • Learn how to get Started with Raspberry Pi from Scratch

  • Discover various Object Detection models

  • Introduction to Deep Learning and Tensorflow lite

Instructors

Profile photo of Augmented Startups
Augmented Startups

So a bit about me, Ritesh Kanjee: I've graduated from University of Johannesburg as an Electronic Engineer with a Masters in Image Processing and 8 years ago I started my online school called Augmented Startups where I have over 100'000 subscribers on YouTube and over 60'000 students on Augmented AI Bootcamp/Udemy.I’ve worked with popular tools such as TensorFlow Keras, Open...

Instructors

Profile photo of Laszlo Benke
Laszlo Benke

I am an electrical engineer, I work as a Python software engineer freelancer. I use Raspberry Pi and Computer vision technologies (AI, Object detection CNN) in my projects. You can find me on Upwork (freelancer projects) and Codementor (live teaching) also, for further information.Experienced Project Specialist with a demonstrated history of working in  the industrial automation industry. Skilled in Embedded ...

Review
4.9 course rating
4K ratings
ui-avatar of Manikanta Swamy Seeripi
Manikanta S. S.
5.0
2 years ago

nice

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ui-avatar of Tmauldin
Tmauldin
1.0
2 years ago

The video is out of focus. Tried 2 machines same result, out of focus. This is not a learning course, it is a wanna be instructor. I have purchased many Udemy courses and this is pathetic.

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ui-avatar of arm arm
Arm A.
1.0
3 years ago

poor course and not worth to be watched

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ui-avatar of Enrico Monti
Enrico M.
4.5
4 years ago

Era adatto a me. Ottimo Corso.

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ui-avatar of Robert
Robert
2.0
5 years ago

Very knowledgable but is going too fast and the transcript is really miserable. Could not figure out what is CNN! explain. I think having a framework which is shared at the begining would have been helpful.

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ui-avatar of Luis Antonio Flores chacayan
Luis A. F. C.
4.0
5 years ago

good

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ui-avatar of Mickey Cohen
Mickey C.
2.5
5 years ago

Huge amount of facts but impossible to digest.

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ui-avatar of Diego Galindo
Diego G.
2.0
5 years ago

Instr

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ui-avatar of James Bishop
James B.
1.0
5 years ago

I can't proceed past lecture 14 as the installation instructions fail.

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ui-avatar of Alvaro David Orjuela Cañón
Alvaro D. O. C.
3.0
5 years ago

Las partes de programación pasan muy rápido, sin tiempo de digerirlo. Por otra parte, los videos sobre ANN son más ilustrativos y entendibles.

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