What are you learning?
- Learn how to complete 26 advanced computer vision projects, including Emotions, Age and Gender Rating, London Underground Signs, Monkeys, Flowers, Fruits, The Simpsons Role and more!
- Using advanced computer vision technologies such as transfer learning, pre-trained models (VGG, MobileNet, InceptionV3, ResNet50) for deep learning and popular CNNs such as AlexNet, LeNet, VGG and U-Net.
- Understand how to navigate neural networks, convincing neural networks, R-CNNs, SSDs, YOLOs, and GANs with easy-to-follow tutorials.
- Learn about other frameworks (PyTorch, Caffe, MNET, CV APIs) and cloud GPUs, and get a glimpse into the world of computer vision.
- How to Use Compass Deep Python's Library to Build Complex Deep Learning Networks (Using Tensor Flowbacks and)
- How to transmit neuropods, use deep vision and GAN for faces up to 60+.
- How to create, name, describe, or train your best picture data set for university plans and initiatives
- How to use Open CV with free option with about 4 hours of video.
- How to use CNNs such as U-Net to perform image distribution, which is very useful in medical imaging applications?
- How to use the TensorFlow ۾ Object Detection API and create custom object detector in YOLO
- Face recognition with VGGFace
- Use Cloud GPUs to increase CPU speeds up to 100 times on PaperSpace.
- Create and host computer vision APIs and web applications on AWS using EC2 examples.
Requirements
Basic programming knowledge is a plus, but not required.
High school level math, college level is a bonus.
At least 20 GB of storage space for virtual machines and data sets
A Windows, MacOS or Linux operating system
Attribute
Updated: June 2020
TensorFlow 2.0 compatible code
Windows Installation Guide for TensorFlow2.0 (with Keras), OpenCV4 and Dlib
Deep Learning Computer Vision ™ CNNs, YOLOs, TFODs, R-CNNs, SSDs, and GANs + A free introduction to OpenCV implementation Read and use Kerross.
If you would like to learn the latest 2019 concepts for applying Deep Learning on Computer Vision then look no further - this course is for you! In the Deep Learning framework, you will find the following:
To a
Tensor Current 2.0
TensorFlow Object Detection API
Yolo (Dark Net and Dark Flow)
Open CV4
All in one easy-to-use virtual machine, pre-installed with all libraries!
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April 2019 Update:
How to configure the Cloud GPU on PaperSpace and train CIFAR10 AlexNet CNN nearly 100 times over!
Build the Computer Vision API and the Web App and host on AWS using the EC2 model!
Updated March 2019:
Newly added face recognition and credit card number reader project
Identify many people using your webcam.
Face recognition on characters from friends' TV shows
Take pictures of credit cards, draw numbers on the cards and identify them!
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Computer vision applications, including deep learning, are on the rise!
Having machines that can 'lead' will change our world and revolutionize almost every industry out there. Machines or robots can see:
Perform surgery and accurately diagnose and diagnose with medical scans.
Enable automated driving cars.
Basically changing robots allow us to create robots that can help us with anything, clean and almost anything.
Understand what happens when hosting CCTV surveillance video, as well as security, traffic management and other services.
Create art with stunning neural style transitions and other sophisticated image types.
Duplicate many features such as aging faces, switching live video feeds and actually turning actors into movies.
Big tech companies like Facebook, Google, Microsoft, Apple, Amazon and Tesla spend billions on computer vision research.
As a result, the demand for computer vision specialists is growing rapidly!
However, deep dreams can make computer dreams difficult to learn!
The lessons are very technical and theoretical.
The code is out of date.
Beginners don't know where to start.
So I took this course!
I spent months devising a proper and thorough learning path.
I learn the most important concepts logically and without the heavy burden of mathematical ideas using the latest methods.
I've created a free virtual machine with all Deep Learning libraries (Cara, Tensor Flow, OpenCV, TFODI, Yolo, DarkFlow, etc.)! This will save you hours of complicated installation.
I teach based on practical examples and you can learn 18 projects!
Projects such as:
Handwritten numeric rating using MNIST
Image rating using CIFAR10
Cat vs. cat rating
Flower classification with flowers-17
Fashion Rating with FNIST
Category of monkey breeds
Fruit classification
An overview of the role of Simpson
Use the pre-trained image mesh model to classify up to 1000 object segments
Age, gender, and emotion rating
Nucleus Detection in Medical Scans with U-Net
Object Identification Using the ResNet50 SSD Model Using Tensor Flow Object Id
Find Items With YOLO V3
A customer is searching for underground signs of the YOLO object detector London.
Immersive dream
Neurological disorders
GANs - Generate fake statistics.
GANs - Age up to 60+ faces with Age-cGAN
Facial recognition
Digital Credit Card Reader
Using Cloud GPUs on PaperSpace
Build the Computer Vision API and the Web App and host on AWS using the EC2 model!
And OpenCV projects like:
Live sketches
Identification of the shapes
Computer circle and ellipse.
Find the wall.
Single object detector with OpenCV
Car & Pedestrian Detector With Cascade Classifier
So if you are looking for a good foundation in computer vision, look no further.
This is the course for you!
In this course, you will discover the power of computer vision in Python and the skills needed to dramatically improve your career prospects as a computer vision developer.
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For updates and support:
I'll be active in the Q&A area of the daily course, so you'll never be alone.
So, you're ready to get started
Here is the download links
https://www.udemy.com/course/master-deep-learning-computer-visiontm-cnn-ssd-yolo-gans/
https://drive.google.com/file/d/1KguDDG7x7jzLAGEZB9qFYwXRl3H5DQ95/view?usp=sharing
* If your in trouble watch the video thanks! *
Torrent software for windows -> Torrent Downloader
you can join over whats app group -> FREE COURSES 2022
