shreyasvedpathak / Tensorflow-Advanced-Techniques-Solutions

This repository contains my solutions for the Coursera course TensorFlow: Advanced Techniques Specialization. Expand your knowledge of the Functional API and build exotic non-sequential model types. Learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. Explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs.

Tensorflow : Advanced Techniques Solutions

This repository contains my solutions for the Coursera course TensorFlow: Advanced Techniques Specialization.

Incase any of the notebooks are not visible on GitHub, open in Colab:

Course 1: Custom Models, Layers, and Loss Functions with TensorFlow

• Week 1: Multiple Outputs Model using Keras Functional API.
• Week 2: Creating Custom Loss Functions.
• Week 3: Implement a Quadratic Layer.
• Week 4: Create a VGG Network.
• Week 5: Custom Callbacks.

Course 2: Custom and Distributed Training with TensorFlow

• Week 1: Basic Tensor Operations.
• Week 2: Breast Cancer Prediction.
• Week 3: Horse or Human?
• Week 4: Distributed Training.

Course 3: Advanced Computer Vision with TensorFlow

• Week 1: Bird Boxes.
  
• Week 2: Zombie Detector.
  
• Week 3: Image Segmentation of Handwritten Digits.
  
• Week 4: Dogs vs Cats Saliency Maps.
  

Course 4: Generative Deep Learning with TensorFlow

• Week 1: Style Transfer Dog.
  
• Week 2: AutoEncoder Model Loss and Accuracy.
  
• Week 3: Anime Faces.
  
• Week 4: Generated Hands.