4.30 (153 reviews)
☑ Learn how to get Started with Raspberry Pi from Scratch
☑ Discover various Object Detection models
☑ Introduction to Deep Learning and Tensorflow lite
☑ Implement Object Detection using Movidius NC SDK
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.
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.
Introduction to the Course
Introduction to the Course
Hardware Requirements for Deep Learning
How to take this course.
Frequently Asked Questions (FAQ)
The Super Simple Way to Get Started with Raspberry Pi
How to Install Raspbian Operating System on Raspberry Pi
Optional - Headless Raspberry Pi setup
Initial Raspbian OS Setup on Raspberry PI
4 Raspberry Pi/Linux Scripting Tricks
Deep learning Fundamentals (theory)
Multilayer Perceptron - Artificial Neural Network (Theory)
Convolutional Neural Network (Theory)
Object Detection Models that AI Engineers Use
Tensorflow lite introduction and ARM Machine learning
Top 3 Object Detection Models
How to implement Object Detection using Intel Movidius Neural Compute Stick
Movidius install on Raspberry Pi
How to use Movidius NCAppZoo
What is Darkflow and How to Install It
Setting up and Testing YOLO
Setup GUI and VNC
Implementing Mobilenet SSD
[BONUS] How to Detect Age and Gender on Camera
Bonus: CPU Inference and Model training
OpenCV CPU inference
Introduction how to train a model on custom objects
[BONUS] Recurrent Neural Networks (Theory)
Cool Resources for Students
[NEW] XR Developers Podcast with Ritesh Kanjee
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.
Las partes de programación pasan muy rápido, sin tiempo de digerirlo. Por otra parte, los videos sobre ANN son más ilustrativos y entendibles.
The explanations for the installation and use of the Intel Movidius compute stick are not very involved, there are several configuration parameters that he changes without explaining why or what they mean. There is not a good explanation of how or why the compute stick improves the performance of the pi for ML. The use of the compute stick represents less than than 50 percent of the total duration of the course, the rest are introductory machine learning videos.
You should focus on students so that they can actually learn from the "process" instead of showing off what you know.
Brief but to the point gives you enough information to get started and is a little easier then the online documentation by Intel
Muy flojo, presenta varias ideas pero las trata de manera superficial. La otra mitad del curso es una colección de recetas para instalar el entorno y varias demos. Solo aplica para la versión 1 de neural compute stick.
The theories were good but how it was applied was not aligned. The application portion was about installing and setting up the RPi and movidius. not much was also discussed about it except installation instructions.
it was correct and godd lecture. It was a little bit fast but I will check it more to understand it clearly.
I was able to finish all the experiments. Learn how to use Movidius with videos to detect objects. For me, it was a fun experience. Laszlo is a good instructor. thank you for your insights and valuable resources. Best regards,
This course does not support the new version (v02) of the Movidius, now called exactly 'Neural Compute Stick 2'. Also this new hardware does not (yet) support any RPi Linux-dist. This should have been clearly stated in the course description. (I´ll refund the course.) Other than that it was ok. Not deep though, just a brief intro. More info here; https://ncsforum.movidius.com/discussion/1302/intel-neural-compute-stick-2-information
Quick intro to the Movidius on Raspberry. Everything works as described. Very nice theoretical chapters on Neural Networks.
Good mix of theory and practical - I especially enjoyed the level at which the theoretical components were presented. Not too in depth on the low level theory - just the right level. Lot of components installed that I wouldn't mind a little more info on - but I'm waiting for the Movidius. Hopefully I can reach out to Laszlo when the unit arrives if still unclear on those components. Even the bonus material was intriguing and pleasant surprise. Great course - thank you. Now I'll have to find your RNN course based on the bonus content!!!