Udemy – Deep learning for object detection using Tensorflow 2 2020-11

Description

Deep learning for object detection using Tensorflow 2 is the name of a course to understand, train and evaluate the Faster RCNN, SSD and YOLO v3 models using Tensorflow 2 and the Google AI platform. This course is designed to teach you how to learn and evaluate your in-depth learning object models, especially the Faster R-CNN, SSD and YOLO models. For each of these models, you will first see how they work. This will help you build your vision of how they work. You will then learn how to use the power of Tensorflow 2 to train and evaluate these models on your diagnostic device.

What you will learn in the Deep learning course for object detection using Tensorflow 2

How Faster RCNN Deep Neural Networks Work

How deep SSD neural networks work

How YOLO Deep Neural Networks Work

How to use the Tensorflow 2 object detection API

Train and evaluate deep neural networks to detect objects such as Faster RCNN, SSD and YOLOv3 using your own data

Freeze your model to reach a final model that is ready to be presented

How to use your frozen model to predict a number of images using openCV and Tensorflow 2

How to use the Google Cloud AI platform to teach object recognition models on powerful cloud graphics cards

Use Tensorboard to visualize the development of the loss function and the average amount of accuracy of your model

Change the parameters to improve the performance of your model

Course information

Publisher: Udemy Instructor: Nour Islam Mokhtari English language Level of education: Intermediate Number of lessons: 68 Duration: 9 hours and 16 minutes

Prerequisite

You need to have a basic level of Python (if you know what classes and functions are then you are good to go!)

You need to have a basic understanding of what Tensorflow is.

You don’t need any prior understanding of what object detection is, this is the mission of the course!

Installation

After Extract, watch with your favorite Player.

English subtitle

Quality: 720