./episode_40.sh

Do it with passion or not at all.

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Machine Learning for Fluid Mechanics

This paper outlines fundamental ML methodologies and discuss their uses for understanding, modeling, optimizing, and controlling fluid flows. The strengths and limitations of these methods are addressed from the perspective of scientific inquiry that considers data as an inherent part of modeling, experiments, and simulations.

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FEBio - Multiphysics Finite Element Simulations in Biomechanics & Biophysics

FEBio is a software tool for nonlinear finite element analysis in biomechanics and biophysics and is specifically focused on solving nonlinear large deformation problems in biomechanics and biophysics. Aside from structural mechanics, it can also solve problems in mixture mechanics (i.e. biphasic or multiphasic materials), fluid mechanics, reaction-diffusion, and heat transfer.

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FEM Book by NASA

The Book is an online library of useful information regarding finite element analysis, such as How-To's and engineering theory.

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Upcoming Podcast

For the upcoming podcast I am very happy to welcome Dr. Sarah Kaiser to my show!

Sarah is currently a technical staff member and quantum community lead at Unitary Fund and has spent much of her career developing new quantum hardware in the lab. From building satellites to hacking quantum cryptography hardware, communicating what is so exciting about quantum is her passion. She loves building new demos, tools, and partnerships to help enable the quantum open-source community to grow. When not at the keyboard she loves kayaking, laser cutting everything (safe), and writing books about engineering for kids and adults alike.

In this podcast, we talked about:

  • Quantum Computing (QC) ⚛️

  • Ethics in QC 📙

  • Q# and Sarah’s book about Q# 📚

  • “Quantum Supremacy”

  • and much more…

Went Live This Week


Book of the Week

Graph Neural Networks in Action

In Graph Neural Networks in Action you’ll create deep learning models that are perfect for working with interconnected graph data. Start with a comprehensive introduction to graph data’s unique properties. Then, dive straight into building real-world models, including GNNs that can generate node embeddings from a social network, recommend eCommerce products, and draw insights from social sites. This comprehensive guide contains coverage of the essential GNN libraries, including PyTorch Geometric, DeepGraph Library, and Alibaba’s GraphScope for training at scale.

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Visualize Ideas

Confidence is calm. Arrogance makes a lot of noise.

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Meme of the Week

The struggle is real.


Closing Remarks

If you have any wishes for video topics, you can submit them in this form. Apart from that you can always reach out to me via Twitter or Instagram or LinkedIn, so let’s connect!

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See you next week and in the meantime, make sure to keep engineering your mind!

Jousef