Convolutional Neural Networks in TensorFlow


Software developers who wants to build scalable AI-powered algorithms, need to understand how to use the tools to build them. This course is part of the TensorFlow Developer Certification and will teach the best practices for using TensorFlow, a popular open-source framework for machine learning.

In this course, one learns advanced techniques to improve the computer vision model built in Course 1, by exploring how to work with real-world images in different shapes and sizes, visualizing the journey of an image through convolutions to understand how a computer “sees” information, plotting loss and accuracy, and exploring strategies to prevent overfitting, including augmentation and dropout. Finally, Course 2 introduces transfer learning and how learned features can be extracted from models.

Aditya Jyoti Paul
Aditya Jyoti Paul
Computer Vision and Image Encryption Researcher

My work makes machines smarter, secure and more accessible. I’m passionate about research, teaching and blogging. Outside academia, I love travel, music, reading and meeting new people!