Three Ways to Make Animated Graphs in Python
Learn three simple techniques for creating animated graphs in Python using matplotlib and vpython, from basic to advanced methods.
Using a Bunch of Balls to Model the Ideal Gas Law in Python
Model the ideal gas law with bouncing balls in Python and calculate pressure and temperature.
Using Python to Calculate the Gravitational Field for a Hollow Earth
Calculate the gravitational field of a hollow Earth using Python, exploring its effects on surface gravity and comparing to real-world experiments.
Which String Breaks First? Modeling a Physics Demo with Python
Model a physics demo of two strings supporting a mass using Python to determine which string breaks first when pulled.
Magnetic Field due to a Loop of Current - Python Calculation Included
Derive the magnetic field from a current loop and perform numerical calculations using Python, enhancing understanding of electromagnetic principles.
Finding the Value of Pi from a Random Walk Using Python
Explore Python coding to calculate pi using random walks, from 1D to 3D simulations. Enhance mathematical understanding through practical programming.
Solving a Boundary Value Problem with the Finite Difference Method - Python
Implement finite difference method in Python to solve boundary value problems for differential equations. Learn practical numerical techniques.
Physics Informed Neural Networks - BC Incorporation
Explore Physics Informed Neural Networks and learn techniques for incorporating boundary conditions in these advanced machine learning models.
Code Walkthrough for PINNs in Burgers Equation
Explore Physics-Informed Neural Networks (PINNs) applied to the Burgers equation through a detailed code walkthrough.
Physics Informed Neural Networks - Introduction
Explore the fundamentals of Physics Informed Neural Networks in this concise introduction.
Accelerating Python Code with Numba and CuPy for Machine Learning
Boost Python code execution with GPU acceleration and compilation using Numba and Cupy for machine learning tasks.
How to Install Conda for Data Science and Machine Learning
Aprenda a instalar Anaconda y dominar los entornos conda para ciencia de datos y aprendizaje automático.
Optimizing Python Code Speed with Numba JIT Compiler
Accelerate Python code execution using Numba's JIT compiler, leveraging jit and njit decorators for enhanced performance.
Berkeley Lab's Breakthroughs in Exascale Supercomputing and AI Energy Efficiency
Explore Berkeley Lab's journey from atomic age to supercomputing forefront. Discover exascale computing challenges, energy efficiency innovations, and future HPC directions with specialized hardware and chiplets.
SciFM24 Summer School Opening Remarks
Explore the SciFM24 Summer School with opening remarks from Karthik Duraisamy, gaining insights into the program's objectives and structure.
Introduction to Numerical Computation Applications Using Ubuntu WSL
Explore numerical computing on Ubuntu WSL for efficient solver development and deployment, with practical examples and insights on streamlining workflows for complex engineering problems.
Accelerating Scientific Discovery with AI and Quantum Computing
Explore cutting-edge insights on distributed computing and AI from IBM's Dario Gil in this Ray Summit 2022 keynote address.
Fortran Optimization for Accelerator Devices - Data-Centric Representation
Explore data-centric optimization techniques for Fortran code on accelerator devices, enhancing high-performance computing capabilities.
Using Jupyter and Submitting Your First Homework - ME5180
Learn to use Jupyter Notebooks and submit your first homework assignment in this practical guide for ME5180 students.
Functions, Docstrings, and Working in Jupyter - ME3255 Homework 1
Learn to create functions, write effective docstrings, and navigate Jupyter notebooks for efficient coding and documentation in engineering applications.
Model Reparametrization with StructuralIdentifiability.jl - JuliaCon 2024
Explore StructuralIdentifiability.jl's new features for rapid identification of identifiable functions and model reparametrization, enhancing modeling and control practices.