CS480/680 Winter 2023 - Introduction to Machine Learning

GPU and TPU Acceleration

For GPU and TPU acceleration, feel free to use Google's Colaboratory environment. This is a free cloud service where you can run Python code (including TensorFlow and PyTorch, which are pre-installed) with GPU or TPU acceleration. A virtual machine with two CPUs and one GPU or TPU will run up to 12 hours after which it must be restarted. The following steps are recommended:

• Create a Python notebook in Google Colab
• Click on "edit", then "notebook settings" and select "None" (CPU), "GPU" or "TPU" for hardware acceleration.

Textbooks

There are many good references for machine learning. We will cover material in different textbooks. Most textbooks are freely available online. Complementary readings in the textbooks are indicated for every lecture in the course schedule.

• [ZLLS] Aston Zhang, Zack C. Lipton, Mu Li, Alex J. Smola, Dive into Deep Learning (forthcoming)
• [GBC] Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learning (2016)
• [D] Hal Daume III, A Course in Machine Learning (2017)
• [M] Kevin Murphy, Probabilistic Machine Learning: An Introduction (2022)
• [B] Christopher Bishop, Pattern Recognition and Machine Learning (2006)