This course is focused in the application of Deep Learning for image classification and object detection. This course originally was designed in TensorFlow version 1.X but now the lessons and codes were updated with TensorFlow version 2.X, mainly by the use of Google Colaboratory(Colab).
If you dont have an available GPU in your local system or you want to experiment in an environment without any previous installation or setup, dont worry you can follow the course smootly because all codes were optimized in Google Colab.
The course starts with a concise review of the main concepts in Deep Learning, because this course focused in the application of Deep Learning in the computer vision field.
The main computer vision tasks covered in this course are image classification and object detection.
After reviewing the deep learning theory you will enter in the study of Convolutional Neural Networks (ConvNets) for image classification studying the following concepts and algorithms:
– Image Fundamentals
– Loading images in TensorFlow
– The building blocks of ConvNets such as:
Image Augmentation, etc
– Different ConvNets architectures such as:
– Many practical applications using famous datasets such as:
Courses : 3
Specification: Deep Learning for Computer Vision with TensorFlow 2
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