Tensorflow: Advanced Techniques

Personal Repository for Labs and Assignments related to Tensorflow: Advanced Techniques Specialization from Coursera

• Course 1: Custom Models, Layers, and Loss Functions with TensorFlow
• Course 2: Custom and Distributed Training with TensorFlow
• Course 3: Advanced Computer Vision with TensorFlow
  • Week 1: Introduction to Computer Vision
    • Transfer Learning
    • Network Architectures
  • Week 2: Object Detection
    • R-CNN (FAST, FASTER)
    • TFHub
  • Week 3: Image Segmentation
    • FCN
    • U-net model
    • Instance Segmentation
  • Week 4: Visualization and Interpretability
    • Class Activation Maps (CAM)
    • Saliency
    • GradCAM
• Course 4: Generative Deep Learning with TensorFlow
  • Week 1: Neural Style Transfer
    • Visual interpretations of CNNs
    • NST model architecture
  • Week 2: AutoEncoders
    • Basic AutoEncoders with Dense Layers
    • Convolutional AutoEncoders
    • Image Denoising
  • Week 3: Tuning AutoEncoders
    • Variational AutoEncoders (VAE)
    • Kullback–Leibler divergence
  • Week 4: Generative Adversarial Networks (GAN)
    • Intro to GANs
    • Deep Convolutional GANs (DCGAN)