Welcome to the assignments section of Math 264! Here, the main goal is solving Linear Algebra problems using Python and eventually using it to solve applied problems.
Each assignment in this series focuses on different aspects of linear algebra, integrating Python programming. They are structured to progressively enhance your skills and comprehension in the subject.
-
Assignment 0: Solving a System of Equations Visually and Algebraically with Python
- 🚀 An introductory assignment to get you started with Python and basic linear algebra concepts.
- 🔗 View the related Google Colab notebook here.
-
- 🔍 Focuses on vectors and performing various operations using Python.
- 🔗 View the related Google Colab notebook here.
-
Assignment Two: Python Basics for Linear Algebra
- 🧮 Delves into matrices, their properties, and applications in transformations.
- 🔗 View the related Google Colab notebook here.
-
Assignment Three: Number of Solutions for a System of Equations
- 📈 Explores eigenvalues and eigenvectors and their significance in data science.
- 🔗 View the related Google Colab notebook here.
-
Assignment 4: Spanning, Linear Independence, and Basis
- 🌐 Covers spanning sets, linear independence, and basis in vector spaces.
- 🔗 View the related Google Colab notebook here.
-
Assignment 5: Matrix Multiplication in Python
- 🧮 Focuses on implementing matrix multiplication using both a custom method and NumPy's built-in function.
- 🔄 Tests both methods with matrices of different sizes to ensure correct implementation.
- 🔗 View the related Google Colab notebook here.
- These projects focus on real-world applications of linear algebra concepts using Python. They are designed to bridge the gap between theory and practical implementation.
- Examples include analyzing sports data using the Massey Rating System and exploring probabilistic models with Markov Chains.
- 🔍 Explore the concept of Markov Chains and their applications in various fields.
- 📈 Use Python to model and analyze probabilistic processes with Markov Chains.
- 🧪 Gain insights into stochastic processes and their representation using linear algebra.
- 🏈 Dive into sports analytics by applying the Massey Rating system to evaluate team performances.
- 🧮 Utilize Python to analyze real sports data and compute Massey ratings.
- 📊 Develop skills in data handling, matrix operations, and linear algebra applications.
- 🔗 Slides
- 🔗 NFL Dataset
- Each PDF assignment includes tasks, objectives, and specific guidelines or prerequisites.
- Use Google Colab or your preferred Python environment for these assignments.
- Adhere to the submission guidelines detailed in each assignment.
- Share your Google Colab notebook link or submit your Python script as instructed.
- Ensure your submissions are well-documented and include comments for clarity.
- Refer to the notes and resources linked within each assignment for further reading and clarification.