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❤️ My Favourite Things
🛠️ Tool of the Week
I usually have 100+ browser tabs open which can be super annoying!
Give your memory a boost with Heyday, the research tool that automatically saves the content you view, and resurfaces it within your existing workflows. It’s like cheat codes for your memory!
🎥 YouTube Video
🖊️ Item - Philips Hue White & Colour Ambience LED Table Light
🏫 Course - One Free Month of Skillshare to explore your creativity with classes in illustration, photography, design, productivity and more!
💬 “Education is the passport to the future, for tomorrow belongs to those who prepare for it today.” – Malcolm X
💦 The Potential of Machine Learning to Enhance Computational Fluid Dynamics
Machine learning is rapidly becoming a core technology for scientific computing, with numerous opportunities to advance the field of computational fluid dynamics. This paper highlights some of the areas of highest potential impact, including to accelerate direct numerical simulations, to improve turbulence closure modelling, and to develop enhanced reduced-order models.
🤓 Mathematicians Derive the Formulas for Boundary Layer Turbulence 100 Years After the First Formulation
Turbulence makes many people uneasy or downright queasy. And it's given researchers a headache, too. Mathematicians have been trying for a century or more to understand the turbulence that arises when a flow interacts with a boundary, but a formulation has proven elusive.
🧠 ML by Georgia Tech (Free Course)
The first part of the course covers Supervised Learning, a machine learning task that makes it possible for your phone to recognise your voice, your email to filter spam, and for computers to learn a bunch of other cool stuff.
In part two, you will learn about Unsupervised Learning. Ever wonder how Netflix can predict what movies you'll like? Or how Amazon knows what you want to buy before you do? Such answers can be found in this section!
📚🎓 5 Student Tips in 60 seconds.
🎙️Podcast
📚 Book of the Week
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow
Explore the machine learning landscape, particularly neural nets
Use Scikit-Learn to track an example machine-learning project end-to-end
Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
Use the TensorFlow library to build and train neural nets
Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
Learn techniques for training and scaling deep neural nets
🎬 Animation of the Week
🙃 Meme of the Week
Bruh.
✍️ 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!
Join the Discord server where you can connect with like-minded people.
For any business related issues or collaborations, feel free to write me an email to engineeredmindbusiness@gmail.com!
See you next week and in the meantime, make sure to keep engineering your mind!
Jousef
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