Deep Learning for Computer Vision with TensorFlow 2 Course

ConvNets, ResNet, Inception, Faster R-CNN, SSD, TensorFlow Object Detection, YOLOv4, License Plate OCR

This course is focused in the application of Deep Learning for image classification and object detection. This course includes a review of the main lbraries for Deep Learning such as Tensor Flow and Keras, the combined application of them with OpenCV and also covers a concise review of the main concepts in Deep Learning. We will also enter in the study of Convolutional Neural Networks for image classification reviewing different robust architectures.

We will explore the concepts of Object Detecting and Transfer Learning using the last state of the art algorithms for object detection such as TensorFlow Object Detection API and YOLO, applying this models on images, videos, and webcam images. Finally you will learn how to construct your own dataset.
You will find in this course a consice review of the theory with intuitive concepts of the algorithms, and you will be able to put in practice your knowledge with many practical examples.

Best Seller Course: Deep Learning A-Z™ 2023: Neural Networks, AI & ChatGPT Bonus

What you’ll learn

• Learn about the state of the art models in object detection and image classification models.
• You will learn the theory behind different algorithms in computer vision in a concise way.
• You will be able to deploy your own applications in Computer Vision
• How to collect image data from different resources

Recommended Course: PyTorch for Deep Learning in 2023: Zero to Mastery

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