ENGR108: Introduction to Matrix MethodsJohn Duchi
Stanford University, Fall 2024
Homework is assigned weekly, and due by Thursday at 5:00 PM. We will use gradescope for homework submission. Contact the teaching team if you do not see the class in your gradescope dashboard. Late homework will not be accepted. However, we will drop your lowest homework grade when finalizing grades for the course. The homework problems are assigned from the book, or from the additional exercises (marked with A, as in A2.1), which can be found here. We will update these additional exercises during the quarter, so be sure to download the newest version before starting your homework. Some homework problems will require you to code in Julia (see our Julia page for more information). You must submit your code for any problems that require coding. The Julia files needed for homework problems are available to download here. If you wish to solve problems in Python, you should feel free to do that instead. We recommend that you use Google Colab for these exercises, since it requires the least amount of setup, but you can use any method for running Python that you'd like. You must submit your code with outputs for any problems that require coding. We will do our best to provide Python files for any homework problems, but in the worst case, translating from Julia to Python isn't too hard. You are welcome to collaborate on the homework, but you must write up your own final version to hand in, and you must write up your own code. We strongly recommend against using generative AI software, as it will leave you ill-prepared for the midterm and final exams. If you do use it, please acknowledge it as you would any other source. Homework
Additional exercisesLinked here. You may need to download this regularly, as we will update them. |