HOW YOU CAN BE A PRO YOLOv4 AI OBJECT DETECTION DEVELOPER IN 2 WEEKS
Learn how you can Implement and Train your own Custom YOLOv4 Object Detection models all in 14 Days with my YOLOv4 Course in Computer Vision...
Here's the hard truth about becoming a developer in AI that no one will tell you...
I started out wanting to learn AI in computer vision...
... I used to check a lot of GitHub repos, they were very vague and required for me to be competent in software development/programming and understand all of the jargon –
Now even though I have a masters degree in electronic engineering. It was still challenging for me to figure out. I had a lot of questions like...
- ...What to do to get my code working?
- Do I have the right hardware
- Windows or Linux – If linux, do I use Ubuntu, Red Hat, CentOS, ROS
- If Ubuntu, what version 16.04, 18.04, What kernel do I need?
- If I am training, what format does my dataset need to be in?
- Do I use Python or C++
- If python What dependencies do I need?
- Which frameworks do I use? PyTorch, Tensorflow 1.0 or 2.0
- What commands do I type to infer or train a convolutional neural network
- How big my dataset needs to be?
- How do I run on GPU, and does my GPU support the framework?
I was unsure of what to do. Sometimes I would look at the instructions and because the instructions were so vague, I would skip to the next repo and the next, until I found one that resonates with me or one that had a clear set of instructions that I could understand and follow, or had a video tutorial on it. And video tutorials on this particular topic are very scarce.
The other problem was, I would follow the instructions, but I would run in trivial issues, like not having the correct dependencies or I did not have the correct hardware or OS etc. When things don’t work. This would beat me down and make me loose confidence of whether or not this repository would work. Now I had 2 options, I could either spend tons of hours searching the web to debug the issue or move on to the next repo which also may or may not work.
Then, I thought, if me with a masters degree in electronic engineering had all these issues with getting started in AI, surely other people would be having this same issue as me. People such as:
- non-programmers/non computer science ,
- Hobbyists, Students, researcher, employees.
- People starting out in AI....
Solve Problems
Solve Practical Problems in AI using the computer vision tools. Train your own custom networks
Certainty
Know exactly what hardware, OS, version, tool, Frameworks and commands to use.
Reduced Debugging
Reduce your debugging, because we've already gone through the pain-staking process for you.
Improved Skills
Become skilled in AI so that you are able to charge your clients premium pricing.
Employment
Be more likely to get a job because you have the practical skills and tools that I teach in the course to get you ahead of your competition.
Workflow
Implement an Optimized AI workflow that I use personally, which can accelerate your processes, thus enhancing your productivity.
Guidance
Practice as you learn step-by-step. This course is designed to make AI easy, through tried and tested training that saves you time.
Surety
Be certain that this course will help you or your money back. We also have an exclusive tribe to ask questions and get answers.
But by Following my Step-by-Step Course in AI-Computer Vision, you could:
Okay So... "Is this Course right for me?"
This course is for developers, researchers, and students who have at least some programming experience and want to become proficient in AI for computer vision & visual recognition.
Maybe you:
✔️ Are a computer vision developer that utilizes and are eager to level-up your skills.
✔️ Have experience with machine learning and want to break into neural networks or AI for visual understanding.
✔️ Are a scientist looking to apply deep learning + computer vision algorithms to your research.
✔️ Are a university student and want more than your university offers (or want to get ahead of your class).
✔️ Utilize computer vision algorithms in your own projects but have yet to try deep learning.
✔️ Used AI in projects before, but never in the context of analysis of visual perception.
✔️ Write Python/ML code at your day job and are motivated to stand out from your coworkers.
✔️ Are a "AI hobbyist" who knows how to program and wants to tinker with DIY projects using computer vision.
✔️ You understand that this requires hard work and patience to get the right skills. You understand that you’re going to get any results overnight.
✔️ You’re someone that believes in taking action. You watch the material and then you actually APPLY it.
If any of these descriptions fit you, rest assured: you're the target student.
I designed this course just for you.
Introducing...
A three bundle course — customized to what you want to learn.
Since this course covers a huge amount of content, I've decided to break the course down into three modules called "bundles". A bundle includes tutorial video, activities source code and quizzes for a given module.
1. YOLOv4 Bundle
Implement a Pre-Trained YOLOv4 Model
The YOLOv4 Bundle begins with a gentle introduction to the world of computer vision with YOLOv4, first by learning how to install darknet, building libraries for YOLOv4 all the way to implementing YOLOv4 on images and videos in real-time.
From here you will even solve current and relevant real-world problems by building your own social-distancing monitoring app. You will learn also how to implement vehicle tracking using the robust DeepSORT algorithm.
2. YOLOv4 + PyQT Bundle
Build cross platform interfaces for YOLOv4
The PyQT Bundle is appropriate if you want to take a deeper dive in YOLOv4. Inside this bundle, I cover more techniques and best practices/rules of how to take your python implementations and develop Graphical User Interfaces (GUI's) for your YOLOv4 apps using PyQT. Qt allows you to develop cross platform apps with beautiful interfaces with powerful coding tools.
In this module we will show you how to work with PyQT as well as on how to integrate YOLOv4 models to build your own apps. Speaking of apps we will show you how to detect if a person is wearing their mask (Mask Detection) and develop a GUI to display this information.
3. YOLOv4 + PyQT + Trainers Bundle
How to train your own custom YOLOv4 model
This bundle is the most in-depth bundle and is a perfect fit if you want to natively train your own YOLOv4 neural network. We start you off from the ground-up with labeling your own dataset from scratch with FREE dataset annotation tools.
But there will also be times where you will want to adapt other peoples datasets, we will show you how to convert standard datasets into YOLOv4 format. To amplify your dataset 10x, we employ data augmentation to significantly increase the diversity of available data for training models, without actually collecting new data.
Once we have our data, we prepare our files for training and setup the configuration files. After training, if you want to accelerate the process, we show you how to implement Multi-GPU training. You will also develop your own Mask Detection app to detect whether or not a person is wearing their mask and to flag an alert.
Check out the Apps that you will be Developing in this course.
PLUS... IF YOU PURCHASE TODAY, YOU WILL ALSO GET THIS FAST ACTION BONUSES WORTH $587
Bonus 1 - Neural Networks Fundamentals Nano-Course
This Nano-course teaches you the basics of Neural Networks. It include 3 forms of Artificial Neural Network architectures that are commonly used in AI industry and research. [Worth $99]
Bonus 2 - Accelerate Deep Learning on a Raspberry Pi Course
Get FREE access to the course that will show you how to accelerate your AI Object Detection models 5X faster on a Raspberry Pi 3, using the Intel Movidius for Deep Learning. [Worth $149]
Bonus 3 - Build your own E.D.I.T.H. Glasses AI from Spiderman Course
Project E.D.I.T.H. shows you how to prototype the AI that Tony Stark handed down to Peter Parker in Spiderman (Far from Home). Put your self in the shoes of a superhero as we prototype Stark-Tech in this course. [Worth $199]
Bonus 4 - YOLOv3 Object Detection Course
Even though we are going to be learning the latest YOLOv4, in this YOLOv3 course you get to learn how to implement your training using an optimized workflow called Supervisely. Supervisely allows you to easily label, augment and train your models anywhere without the technical expertise.
[Worth $140]
Course Requirements
Mid-High Range PC/Laptop
Windows 10
NVIDIA CUDA GPU
JUST IMAGINE, 14 DAYS FROM NOW IF...
Imagine, if a week from now, once you have completed this course, that you are able to implement and train your own custom Convolutional Neural Networks (CNN's) with YOLOv4. Imagine all the applications you could do with these skills!
You could be take your new found expertise and be:
- Solving real world problems,
- Freelancing AI projects,
- Getting that job/opportunity in AI,
- Tackling your research guns blazing!
- Saving time, money, &
- Wishing you had done this course sooner.
The world is your oyster... Ask yourself...What cool things would you do once you have skills in AI?
Offer Valid For:
Pricing Options
Select the Bundle that suits you...
YOLOv4 + Trainers + PyQT Bundle
$237
ENROLL NOW
- Everything in YOLOv4 Bundle [$196]
- Everything in PyQT Bundle [$333]
- How to natively train your own custom YOLOv4 detector [$199]
- Dataset Labeling from scratch [$19]
- Dataset Annotation tools [$19]
- Standard Dataset conversion into YOLOv4 format [$59]
- Data Augmentation [$69]
- Preparing files for training & setup configuration files [$29]
- How to Join Datasets [$39]
- Multi-GPU Training [$119]
- Certificate of Completion
- LIFETIME ACCESS
- [Total Value of $1081]
If you have any questions or concerns about the course, contact us below. We're happy to help.
DON'T TAKE MY WORD FOR IT,
HERE'S WHAT PEOPLE ARE SAYING ABOUT MY COURSE & YOUTUBE CHANNEL
.
NOW YOU HAVE TWO CHOICES...
OPTION 1 - GO AT IT ALONE
You can take this knowledge and try to do it by yourself, without a system or a coach. You can waste time debugging, browsing Stack Overflow and Github for that perfect repo that will solve your problems. There is also chance that you may even go backwards. Watch the days go by and wonder “what if…”.
Worse, you’ll watch other people succeed while you struggle to figure it out. Other developers pop out of seemingly out of nowhere suddenly shows off your idea! Something you could have had.
OPTION 2 - TAKE THE FAST LANE AND LEARN AI WITHIN A WEEK
You can follow a PROVEN SYSTEM or hire a mentor, who has been exactly where you are right now, to guide you. Within a week, you will fast track your AI development so that you can start developing practical AI apps that helps solves problems.
This course gives you…
- ..faster results...
- ...support the whole way there...
- ...the opportunity to dramatically upgrade your skills in AI-CV.
SO WHICH OPTION DO YOU WANT TO TAKE? CHOOSE WISELY.
STILL UNSURE? HERE'S SOME COMMON QUESTIONS WE GET...
➤ YES! It’s yours forever!
➤ You’ll get an email from me in which I will give you access to the course.
➤ You’ll have LIFETIME access to it.
➤ You are looking to be spoon fed (you ONLY do what’s covered in a course).
➤ You’re unemployed (unless you have lots of money saved up where you can comfortably join the course. You’re NOT gonna get far if you’re under pressure).
➤ You’re in debt (join the course later once you’re out of it).
➤ You want to put the minimum amount of work to get the maximum results
➤ You understand that this requires hard work and patience to get the right skills. You understand that you’re going to get any results overnight.
➤ You are committed. This course is about developing core skills that will stay with you a lifetime and will be the foundation for your success for YEARS to come.
➤ You’re someone that believes in taking action. You watch the material and follow along step-by-step.
➤ Are a computer vision developer that utilizes and are eager to level-up your skills.
➤ Have experience with machine learning and want to break into neural networks or AI for visual understanding.
➤ Are a scientist looking to apply deep learning + computer vision algorithms to your research.
➤ Are a university student and want more than your university offers (or want to get ahead of your class).
➤ Utilize computer vision algorithms in your own projects but have yet to try deep learning.
➤ Used AI in projects before, but never in the context of analysis of visual perception.
➤ Write Python/ML code at your day job and are motivated to stand out from your coworkers.
➤ Are a "AI hobbyist" who knows how to program and wants to tinker with DIY projects using computer vision.
➤ You understand that this requires hard work and patience to get the right skills. You understand that you’re going to get any results overnight.
➤ You’re someone that believes in taking action. You watch the material and then you actually APPLY it.
➤ Hiring a mentor who charges you $50 an hour. Getting 3 hours of training from them per week would cost you about $600 a month. Its also very challenging to find an AI mentor who will be willing to assist.
➤ This course will save you a lot in time from figuring it out by yourself. Time is money and is especially valuable since we have a limited time on this planet. Do you want to waste it wreaking your brains debugging and figuring this out by yourself?
➤ What would this course be worth to you if it got you even one client? Or what would be your return if you landed a job as an AR developer?
➤ Most of my material is free… But I charge a premium price for the very best stuff.
➤ Lastly, this course is so good you can’t afford to NOT have it.
➤ First of all, Python is awesome. It is an easy language to learn and hands-down the best way to work with deep learning algorithms.
➤ The simple, intuitive syntax allows you to focus on learning the basics of deep learning, rather than spending hours fixing crazy compiler errors in other languages.
➤Don't worry; you won't get swamped by tons of theory and complex equations.
➤We'll start off with the basics where you'll learn in a fun, practical way with code.
➤You'll be an Object Detecting ninja in no time, and be able to graduate to the more advanced content.
➤This course isn't just for beginners — there's advanced content in here too.
➤You'll discover how to train your own custom object detectors using AI.
➤You'll build a custom framework that can be used to train very deep architectures using Yolo V3.
➤ I'll even show you my personal workflow blueprint that I use to determine which AI techniques to apply when confronted with a new problem.
➤Best of all, these solutions and tactics can be directly applied to your current job, research, and projects.
I personally use the NVIDIA 1080 (8GB) on a daily basis for training my own AI models. Alternatively, I would recommend using Amazon EC2 and their GPU instances (particularly p2.* and g2.*) in the cloud to train your networks if you do not want to purchase physical hardware.
It is possible to execute the model on a CPU without a problem. If you are using a GPU will dramatically speed up the network training process. Its best to use an NVIDIA GPU as we use the CUDA libraries which are only compatible with the NVIDIA brand. So please ensure that you are using a CUDA support NVIDIA GPU.
Each bundle builds on top of the others and includes all content from lower modules. You should choose a bundle based on (1) how in depth you want to study AI in computer vision & visual recognition and (2) your particular budget.
We program specifically for Windows 10. We will be releasing a course for Ubuntu later this year.
No - Why reinvent the wheel, this course focuses on the implementation of YOLOv4 to get you up and running. We do NOT build the network layer-by-layer.
➤ If you have any other questions, please send me a message via Facebook Messenger, and I'll get back to you ASAP.
