I just want to ramble about the stuff I'm learning cause I think it's neat.
Wow!
1. Best "beginners' beginning" definition of a topological space I have encountered.
2. It makes the case for the mathematical necessity of topology.
youtu.be/IQqtsm-bBRU?...
#ITeachMath #MathSky
Wow!
1. Best "beginners' beginning" definition of a topological space I have encountered.
2. It makes the case for the mathematical necessity of topology.
youtu.be/IQqtsm-bBRU?...
#ITeachMath #MathSky
Here is how and why I gave this model organism a visual upgrade 🧵(1/7)
Here is how and why I gave this model organism a visual upgrade 🧵(1/7)
www.counting-stuff.com/making-inter...
www.counting-stuff.com/making-inter...
📚 github.com/ryokamoi/llm...
We feature papers & blogs in
* Key self-correction papers
* Negative results in self-correction
* Projects inspired by OpenAI o1
📚 github.com/ryokamoi/llm...
We feature papers & blogs in
* Key self-correction papers
* Negative results in self-correction
* Projects inspired by OpenAI o1
## Building AI systems
• Patterns for Building LLM-based Systems: eugeneyan.com/writing/llm-...
• What We’ve Learned From A Year of Building with LLMs: applied-llms.org
## Building AI systems
• Patterns for Building LLM-based Systems: eugeneyan.com/writing/llm-...
• What We’ve Learned From A Year of Building with LLMs: applied-llms.org
www.bewitched.com/demo/gini
www.bewitched.com/demo/gini
In the meantime, if you are curious how Multimodal LLMs work, I recently wrote an article to explain the main & recent approaches: magazine.sebastianraschka.com/p/understand...
In the meantime, if you are curious how Multimodal LLMs work, I recently wrote an article to explain the main & recent approaches: magazine.sebastianraschka.com/p/understand...
young clark kent: *crumples self portrait*
young clark kent: *crumples self portrait*
Bayesian neural networks address overfitting by modeling uncertainty in the weights. Plus they can be trained using standard neural net tools using an algorithm called stochastic variational inference, which we cover at the end of this tutorial.
Bayesian neural networks address overfitting by modeling uncertainty in the weights. Plus they can be trained using standard neural net tools using an algorithm called stochastic variational inference, which we cover at the end of this tutorial.
Principles and Practices of Engineering Artificially Intelligent Systems
mlsysbook.ai
Principles and Practices of Engineering Artificially Intelligent Systems
mlsysbook.ai
A book on symmetry, with great exposition of univalent mathematics, group theory, geometry and groups, galois theory and more.
unimath.github.io/SymmetryBook...
A book on symmetry, with great exposition of univalent mathematics, group theory, geometry and groups, galois theory and more.
unimath.github.io/SymmetryBook...
How to contribute 👇👇👇
#DLSC #RStats #Python #DataScience @dslc.io
How to contribute 👇👇👇
#DLSC #RStats #Python #DataScience @dslc.io