This repository contains useful files for the advanced machine learning course. It will be updated as the course progresses to include tutorials (python and tensorflow), code samples from lecture, homework assignments, and term-project information.

Can be found here.

In order to ensure that all students are working in a uniform environment, students will be expected to use Colab to follow along with in-class coding examples and solve homework assignments. We will also provide some term-project ideas of an appropriate computational such that the resources provided by Colab will be adequate. An introduction to Colab will be provided with the in-class python_tutorial.

Throughout the course, students will be expected to solve problems and create projects using the Python programming language. Prior knowledge or experience with the language is not assumed and a tutorial covering basic syntax, data structures, and libraries will be provided. Material pertaining to the the tutorial may be found in the python_tutorial folder.

For the second half of the semester, students will be expected to use Tensorflow's Python API in order to construct and train deep neural networks. Once again, prior knowledge or experience using Tensorflow (through the Python or any other API) is not assumed and a tutorial will be provided in lecture. Material pertaining to the the tutorial may be found in the tensorflow_tutorial folder.

PDFs containing the homework assignments may be found in the homeworks folder. Released solutions can be found on courseworks.