Practical

You can download the materials of practical classes here . I will try to upload materials prior to their corresponding classes.

• 

  Introduction to Colab and MLP
  tl;dr: What is colab? How MLP works? and mathematics of backpropagation mechanism
  

  [note] [introduction to colab]
• 

  Preprocessing for text based tasks
  tl;dr: What is preprocessing? What is encoding? one hot encoding and tf-idf encoding and some others encoding
  

  [colab file]
• 

  Preprocessing for image based tasks
  tl;dr: How to get a dataset for image-based tasks? How to prepare an image for feeding into our model?
  
• 

  Visualisation
  tl;dr: How to visualize layers and filters?
  

  [How to visualize convolutional features] [colab file - visualisation filters] [colab file - visualisation heatmap]
• 

  Image augmentation
  tl;dr: What is augmentation? How to augment data in Keras? What is generator?
  

  [How to use data generators with Keras] [Keras data generators and how to use them] [Image Augmentation with Keras - 1] [Image Augmentation with Keras - 2]
• 

  Transfer Learning and Sequence to Sequence Model
  tl;dr: What is Transfer learning? How to use a pretrain model in Keras? What is Sequence to Sequence models and how to implement a machine translation model?
  

  [Transfer learning] [Multi-Task Deep Neural Networks for Natural Language Understanding] [Kaggle Transfer learning] [colab file - Seq2Seq]
• 

  TensorFlow 2 Tutorial
  tl;dr: A set of tutorials, prepared by IUST, on TensorFlow 2 (basically a mini-course): It covers most of the required materials to start coding in TensorFlow, such as defining the computation, designing the model, working the input pipeline, and many more.
  

  [official page]