GitHub / Ankit-Kumar-Saini / Coursera_TensorFlow_Advanced_Techniques_Specialization
Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.
Stars: 9
Forks: 4
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 53.9 MB
Dependencies parsed at: Pending
Created at: about 4 years ago
Updated at: over 2 years ago
Pushed at: almost 4 years ago
Last synced at: about 2 years ago
Topics: auto-encoders, coursera-specialization, custom-layers, custom-loss-functions, custom-model-development, custom-training-loops, functional-api, generative-adversarial-networks, gradcam-visualization, gradient-tape-optimization, image-segmentation, mask-rcnn, model-interpretability, object-detection, retina-net, saliency-map, tensorflow2, variational-autoencoders