Syllabus for CS84: Deep Learning


  • Lesson 1: Introduction to Neural Networks

    In this class we'll learn about the Perceptron as the building block for neural networks and deep learning

  • Lesson 2: Introduction to TensorFlow

    In this class we'll start exploring how to use the TensorFlow library.

  • Lesson 3: More TensorFlow, Intro to Keras

    In this class we'll keep working with TensorFlow and start learning to use Keras.

  • Lesson 4: Working with Images

    In this lesson we'll start learning how to process images with our ML architectures, including running a model for image ID or generation.

  • Lesson 5: Convolutional Neural Networks (CNN)

    Today we'll start exploring a new type of neural network and learn about regularizations

  • Lesson 6: Transfer Learning

    Transfer learning allows us to copy effective parts of existing models. Today we will also introduce the midterm project.

  • Lesson 7: Midterm Project: Image Classification

    Project Day

  • Lesson 8: Finish Midterm Project, presentations

    Students will present their work from the midterm project. Class discussion on topics to cover in Unit 2 in order to meet student goals.

  • Lesson 9: Recurrent Neural Networks (RNNs)

    RNNs can be used to make predictions about time series data, like words in a sentence. Topic may change depending on student goals for Unit 2.