This project is based on CS111 UCSB. The project is an introduction to computational science, emphasizing basic numerical algorithms and the informed use of mathematical software. Matrix computation, systems of linear equations, and differential equations. The whole project is consist of 7 subsections, each has one specific topic to explore. The project process as a record of exploration on fast solution to actual problem based on machine.

• Math prerequisites, linear algebra
• Sepcial Matricss and LU Factorization
• Matrix properties and more Factorization, Cholesky
• Multiple Solvers of Ax = b, discrete way to solve 3-D temperture problem
• Iterative Solver for Ax = b: The Jacobi Method, The Conjugate Gradient Method
• Linear Least Squares; IEEE Floating Point Standards
• Exploration, optimazation of Pagerank
• Solving ODE models with python, Euler and other method, Stiffness of solution

This project is based on Python(version 3.5 or higher), mainly based on 3 packages:

• numpy: Numerical computing with arrays and matrices
• scipy: More advanced numerical computing, including sparse matrices
• matplotlib: Plotting and visualization

Coding and notes are recored on Jupyter notebooks

• This project is based on CS111 UCSB.