Applied Deep Learning Course


Deep Learning (DL) Foundation

  • AI vs ML vs DL
  • Review of ML and DL Fundamentals
  • Neural networks(NN) and Deep Neural Networks (DNN)
  • Introduction to Keras, Tensorflow, and GPU devices
  • Data Preparation for DL
  • Hands On

Convolution Neural Networks (CNN)

  • Computer Vision and CNN Introduction
  • CNN architecture
  • Designing deep CNNs and Training
  • CNN Fine-tuning: Transfer Learning
  • CNN Applications: Object Detection & Segmentation, Image Classification
  • Hands On Project

Recurrent Neural Networks (RNN)

  • Introduction of RNN and LSTM (Long Short Term Memory)
  • Text Representation and Word Embeddings
  • RNN Applications; Text Classification, Text Generation, Photo Caption Generation
  • Hands On Project