📈 An investment in knowledge pays the best interest.
Hey friends & nerds! Welcome to the Sunday Science Newsletter – in this newsletter we explore & discuss strategies, systems & tools that help us become better, smarter and more effective scientists, gadgeteers and thinkers.
❤️ Weekly Favourite Things
🎬 My Favourite Video
Courses – Explore your creativity with classes in illustration, photography, design, productivity and more!
🎙️ Long Short-Term Memory (LSTM) - Sepp Hochreiter | Podcast #76
💻 Introducing nTopology’s New Latticing Technology
nTopology the release of nTopology’s 3rd generation latticing technology, the most advanced lattice generation tool available today!
With nTopology, you can solve the hardest advanced manufacturing and engineering problems, generate unique high-performance parts, share and reuse your workflows with your team, and more.
🧠 Mathematics for Machine Learning
This is a tightly curated collection of free books, videos, and papers for learning mathematics for machine learning. Covers all levels.
Source: GitHub | Elvis Saravia
💻 Engineering Tool of the Week – PyFR
PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures using the Flux Reconstruction approach of Huynh. The framework is designed to solve a range of governing systems on mixed unstructured grids containing various element types. It is also designed to target a range of hardware platforms via use of an in-built domain specific language derived from the Mako templating engine. The current release (PyFR 1.14.0) has the following capabilities:
Governing Equations - Euler, Navier Stokes
Dimensionality - 2D, 3D
Element Types - Triangles, Quadrilaterals, Hexahedra, Prisms, Tetrahedra, Pyramids
📚 Book of the Week
The Kaggle Book: Data Analysis and Machine Learning for Competitive Data Science
The Kaggle Book assembles in one place the techniques and skills you'll need for success in competitions, data science projects, and beyond. Two Kaggle Grandmasters walk you through modeling strategies you won't easily find elsewhere, and the knowledge they've accumulated along the way.
As well as Kaggle-specific tips, you'll learn more general techniques for approaching tasks based on image, tabular, textual data, and reinforcement learning. You'll design better validation schemes and work more comfortably with different evaluation metrics.
🙃 Meme of the Week
Never Underestimate Fluids.
🎬 Animation of the Week
✍️ Closing Remarks
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See you next week and in the meantime, make sure to keep engineering your mind! 🧠