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Week 12

In this lesson, we will explore the future of big data and deep learning.

Objectives

After completing this week, you should be able to:

  • Describe upcoming advances in big data and deep learning and their potential use cases
  • Experiment with advanced deep learning use cases including text and image generation

Readings

  • Chapter 12 in Designing Data-Intensive Applications
  • Read chapters 8 and 9 in Deep Learning with Python

Weekly Resources

Assignment 12

Using section 8.4 in Deep Learning with Python as a guide, implement a variational autoencoder using the MNIST data set and save a grid of 15 x 15 digits to the results/vae directory. If you would rather work on a more interesting dataset, you can use the CelebFaces Attributes Dataset instead.

Submission Instructions

For this assignment, you will submit a zip archive containing the contents of the dsc650/assignments/assignment12/ directory. Use the naming convention of assignment12_LastnameFirstname.zip for the zip archive. You can create this archive in Bash (or a similar Unix shell) using the following commands. 

cd dsc650/assignments
zip -r assignment12_DoeJane.zip assignment10

Likewise, you can create a zip archive using Windows PowerShell with the following command. 

Compress-Archive -Path assignment10 -DestinationPath 'assignment12_DoeJane.zip

Discussion Board

You are required to have a minimum of 10 posts each week. Similar to previous courses, any topic counts towards your discussion count, as long as you are active more than 2 days per week with 10 posts, you will receive full credit. Refer to the optional topics below as a starting place.

Topics include, but are not limited to Kubernetes, deep learning hardware, and cloud computing.

Last update: March 12, 2023