Hello trend,
This is Satya Mallick from LearnOpenCV.com.
In today's blog post, we discuss the different face Recognition algorithms that have emerged over the past years. We will talk about DeepFace by Facebook, FaceNet by Google, VGG-Face from Oxford, and Arcface.
We will also discuss the popular libraries that you can use to build applications using Face recognition technology. We also discuss the different datasets and a general pipeline for Face Recognition.
| Analyzing Face Recognition Algorithms |
We also cover Face Recognition in great detail in our course on Computer Vision II: Applications.
As a prospective learner, you would be happy to know that the Memorial Day Sale for the Official AI Courses by OpenCV is on!
The following 5 courses will be available at a massive discount.
- OpenCV for Beginners
- Computer Vision I: Introduction
- Computer Vision II: Applications
- Deep Learning with PyTorch
- Deep Learning with TensorFlow & Keras
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Not Interested? Click this link to opt-out .
Are our students Happy?
As teachers of the craft of AI, we love the following quote
We got reminded of this quote when Daniel Schaben tagged us in a tweet with his certificate of completion for Computer Vision I.
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Thank you, Daniel, for those beautiful words. Wholly unsolicited and straight from the heart. Priceless!
Here is another post from Israel Raul TiƱini Alvarez who tagged on his LinkedIn post with his certificate of completion.
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The comment was heartwarming because Israel not only called our courses the "best courses in computer vision and image processing," he also called the material intuitive.
We teach because it is very satisfying to see students in our course gain a deep understanding of the material while embarking on a financially rewarding career path. What starts as a spark of interest becomes a blazing fire.
You have 30 days to change your mind with our 30-day no-questions-asked money-back guarantee. You get to keep the book even if you change your mind!
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Frequently Asked Questions
Let's go over some questions you may have before you make a purchase.
#1 I have no experience in Computer Vision or Machine Learning. I am also not good at Math. Are these courses right for me?
Most of our students are software engineers or programmers with no background in Computer Vision. Many make a career switch into AI, and others use the skills they learn in our courses to become better engineers at their current jobs.
In our courses, we teach mathematical concepts so you grasp them at an intuitively level without drowning in mathematical details.
We expect you to have working knowledge of at least one programming knowledge. We have also included Python for Beginners for free. Other than that, there are no prerequisites. We will walk you through the basics.
#2 Can I get a refund if I am not happy with the course?
Yes, you can ask for a full refund within 30 days no-questions asked.
#3 I cannot afford the course. Can I share an account with a friend?
Absolutely! There is just one limitation. If you are eligible for a certificate, we can issue only one per account.
#4 What if I had questions about the material?
We will be in the course forum answering your questions.
#5 How is the material organized?
The content is a mix of theory and code with explanations through Text and Video. Apart from this, we have quizzes, assignments, and projects to give you a full hands-on experience.. You get to choose the projects/assignments that interest you from a collection of available projects/assignments.
#6 How long does it take to complete the course?
Assuming you put in 7-8 hrs/week the expected times to complete our courses are listed below.
OpenCV for Beginners : 1 month Computer Vision I : 3 months. Computer Vision II : 3 months. Deep Learning with PyTorch : 3-4 months. Deep Learning with Tensorflow & Keras: 3-4 months.
#7 How long will I have access to the courses?
How does lifetime access sound? We do this so you can use our courses as reference books you can come back to long after you have completed the courses.
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If you have any further questions, please feel free to ask by replying to this email.
Cheers!
Satya
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