Accelerate Deep Learning on Raspberry Pi
Accelerate Deep Learning on Raspberry Pi, available at $59.99, has an average rating of 3.5, with 25 lectures, based on 162 reviews, and has 1355 subscribers.
You will learn about 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 This course is ideal for individuals who are Students who are serious about Deep learning or Raspberry Pi or Students who are proactive in finding solutions It is particularly useful for Students who are serious about Deep learning or Raspberry Pi or Students who are proactive in finding solutions.
Enroll now: Accelerate Deep Learning on Raspberry Pi
Summary
Title: Accelerate Deep Learning on Raspberry Pi
Price: $59.99
Average Rating: 3.5
Number of Lectures: 25
Number of Published Lectures: 25
Number of Curriculum Items: 25
Number of Published Curriculum Objects: 25
Original Price: $174.99
Quality Status: approved
Status: Live
What You Will Learn
- 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
Who Should Attend
- Students who are serious about Deep learning or Raspberry Pi
- Students who are proactive in finding solutions
Target Audiences
- Students who are serious about Deep learning or Raspberry Pi
- Students who are proactive in finding solutions
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:
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Getting Started with Raspberry Pi even if you are a beginner,
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Deep Learning Basics,
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Object Detection Models – Pros and Cons of each CNN,
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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.
Course Curriculum
Chapter 1: Introduction to the Course
Lecture 1: Introduction to the Course
Lecture 2: Hardware Requirements for Deep Learning
Lecture 3: How to take this course.
Lecture 4: Frequently Asked Questions (FAQ)
Chapter 2: The Super Simple Way to Get Started with Raspberry Pi
Lecture 1: How to Install Raspbian Operating System on Raspberry Pi
Lecture 2: Optional – Headless Raspberry Pi setup
Lecture 3: Initial Raspbian OS Setup on Raspberry PI
Lecture 4: 4 Raspberry Pi/Linux Scripting Tricks
Chapter 3: Deep learning Fundamentals (theory)
Lecture 1: Multilayer Perceptron – Artificial Neural Network (Theory)
Lecture 2: Convolutional Neural Network (Theory)
Lecture 3: Nomenclature
Chapter 4: Object Detection Models that AI Engineers Use
Lecture 1: Tensorflow lite introduction and ARM Machine learning
Lecture 2: Top 3 Object Detection Models
Chapter 5: How to implement Object Detection using Intel Movidius Neural Compute Stick
Lecture 1: Movidius install on Raspberry Pi
Lecture 2: How to use Movidius NCAppZoo
Lecture 3: What is Darkflow and How to Install It
Lecture 4: Setting up and Testing YOLO
Lecture 5: Setup GUI and VNC
Lecture 6: Implementing Mobilenet SSD
Lecture 7: [BONUS] How to Detect Age and Gender on Camera
Chapter 6: Bonus: CPU Inference and Model training
Lecture 1: OpenCV CPU inference
Lecture 2: Introduction how to train a model on custom objects
Lecture 3: [BONUS] Recurrent Neural Networks (Theory)
Lecture 4: Cool Resources for Students
Lecture 5: [NEW] XR Developers Podcast with Ritesh Kanjee
Instructors
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Augmented Startups
M(Eng) AI Instructor 100k+ Subs on YouTube & 60k+ students -
Laszlo Benke
Raspberry Pi expert, Python and AI engineer
Rating Distribution
- 1 stars: 13 votes
- 2 stars: 8 votes
- 3 stars: 30 votes
- 4 stars: 55 votes
- 5 stars: 56 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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