Deep Learning Part 1: 2019 Edition (v3)

Course Materials

Lessons Cover

Many topics, including:

  • image recognition

    • multi-label image classification

    • different kind of images

  • Convolutional Neural Networks (CNNs)

    • image segmentation with U-Net

  • overfitting

  • embeddings

    • collaborative filtering: recommendation systems

  • Natural Language Processing (NLP)

    • language model, sentiment analysis

    • text classification

  • Recurrent Neural Networks (RNNs)

    • RNN architecture from scratch

  • tabular/structured data

    • time-series prediction using neural network

  • CNN architecture

    • back to computer vision

    • CNN in-depth and ResNets from scratch