./episode_155.sh
📚 Teachers open the door, but you must enter by yourself.
💻 The Double Pendulum: MATLAB Code & Implementation
In this MATLAB tutorial, the blog explores the simulation of double pendulum motion - a classic example of chaotic behaviour. The post covers code implementation step by step, explaining parameter definitions, initial conditions, time settings, numerical integration using ODE45, and animation.
💻 1989 Computational Fluid Dynamics Highlights
🏎️ The Science Behind 'Somersault' Crashes & Dangerous Aero
Race car crashes can be horrifying, but none get close to the craziness of those witnessed at the 1999 Le Mans 24 hour race. Seemingly out of nowhere, cars can suddenly flip in the air, with some doing full 360s or others cascading off into or even over the barriers. Read in this blog post what measures modern race cars take to prevent it happening again👇
🧠 Deep Feedforward Neural Networks
AI specialist Jürgen Schmidhuber on the first deep networks, backpropagation and whether you can train a network without unsupervised pre-training.
📚 The Feynman Lectures on Physics
Now, anyone with internet access and a web browser can enjoy reading a high quality up-to-date copy of Feynman's legendary lectures. This edition has been designed for ease of reading on devices of any size or shape; text, figures and equations can all be zoomed without degradation.
💻 Engineering Tool of the Week – OpenSBLI
OpenSBLI is a Python-based modelling framework that is capable of expanding a set of differential equations written in Einstein notation, and automatically generating C code that performs the finite difference approximation to obtain a solution.
This C code is then targetted with the OPS library towards specific hardware backends, such as MPI/OpenMP for execution on CPUs, and CUDA/OpenCL for execution on GPUs.
📚Book of the Week
MATLAB with Python
MATLAB with Python is a book that teaches how to use MATLAB and Python together for technical computing. The book covers some back stories around the evolution of both languages, the basic syntax and data types, and the ways to integrate them (calling Python from MATLAB and MATLAB from Python).
The book also provides examples of using Python libraries for artificial intelligence, such as scikit-learn, TensorFlow, and PyTorch, from MATLAB. The book is intended for engineers and scientists who want to leverage the strengths of both languages and learn from the best practices of each community.
🙃 Meme of the Week
❤️ Support the Blog & Newsletter
🎬 Animation of the Week
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Keep engineering your mind! 🧠
Jousef