My Projects for the specialization of : TensorFlow Advanced Techniques Specialization from deeplearning.ai

• Course 1 : Knowing how to use and customize the TF API.

  • Building multi output model.
  • Using custom layers / models / losses / optimizers / callbacks.
  • Implementing those custom parameters from scratch.
  • Building Vgg / resnet from scratch.

• Course 2 : Applying advanced TF functionalities for effective custom-training processes.

  • Gradient tape usage.
  • Applying custom training loops.
  • Ising Autograph to use the graph-style code instead of Eager Excution.
  • Applying the different strategies for training, depending on the resourcess available.

• Course 3 : Advanced Computer vision techniques related to state of the art models and tasks.

  • Creating an Object localization model from scratch.
  • Using the Object Detection API for inference.
  • Pretraining and using Retina-net for object detection.
  • Building U-net / VGG - FCN-8 encoder-decoder / Mask R-CNN models from scratch and using them for image segmentation.
  • Interpreting the CNNs and how to visualize the performance of each layer in the network using various methods.

• Course 4 : Applying custom-training techniques to build complex Generative models.

  • Building Neural Style Transfere from scratch.
  • Building AutoEncoders and Deep AutoEncoders.
  • Building Convolutional AutoEncoders from scratch and Applying it to several Datasets.
  • Building Variational AutoEncoders from scratch and Applying it to several Datasets.
  • Using VAEs to generate Anime Faces. -needed more like another day of training tho-
  • Building Vanilla-GAN and DCGAN from scratch.
  • Using DCGANs to generate hand sign images.