Deep Learning – Convolutional Neural NetWorks with TensorFlow

Deep Learning – Convolutional Neural Networks with TensorFlow
Duration: 3h 40m | .MP4 1920×1080, 30 fps(r) | AAC, 48000 Hz, 2ch | 877 MB

In the last section, you will learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning for Computer Vision.

By the end of this course, we will have understood how to build convolutional neural networks in deep learning with TensorFlow.

What you Will Learn
Understand the concept of convolution
Integrate convolution into neural networks
Apply CNNs to several image recognition datasets, both small and large
Learn best practices for designing CNN architectures
Learn about batch normalization and data augmentation
Learn how to preform text preprocessing
Audience
This course is designed for anyone interested in deep learning and machine learning or for anyone who wants to implement convolutional neural networks in TensorFlow 2.