Chat GPT's Code interpreter is ready to wipe out 57 BILLION DOLLAR Data analytics market. Here are 10 experiments I carried out using Code interpreter for a Dataset, and the results are INSANE! FOLLOW THREAD BELOW
MACHINE LEARNING
-
Developers competing on AI performance metrics shift toward softer approaches
By
–
For months some developers have been trying to one-up each other using performance evaluation metrics. But some companies may look to use a softer touch. (Free issue)
-
Iterative Parameter Tuning in Machine Learning Model Optimization
By
–
In particular, they "evaluate" by twisting the knobs, so to speak, until they land on a good user experience. If you've worked in data science or ML, that should sound like a very familiar experience.
-
UMAP faster than t-SNE despite being slower than PCA
By
–
Saying UMAP is slower than PCA is "the glass is half-empty" view haha.
The more positive take is: UMAP is much faster than T-SNE! -
Free Foundational Machine Learning Course by Manaranjan Pradhan
By
–
A free foundational course on machine learning by #ManaranjanPradhan. With 20 hours of recorded videos on YouTube, as well as numerous notebooks and exercises, it's useful for anyone looking to start learning about the basics of machine learning. https://
manaranjanp.com/docs/ML-Founda
tion
… -
NeurIPS 2023 LLM Efficiency Challenge and ULMFiT Recommendation
By
–
The NeurIPS 2023 LLM efficiency challenge of course 🙂 https://
llm-efficiency-challenge.github.io Just recommend your Ulmfit paper with @seb_ruder to the students I am collaborating with the other day. Would be looking forward to the solutions you come up with for this one -
Object Keypoint Similarity: Calculation and Scale Handling Explained
By
–
🚀 New Blog Post Alert🚀https://t.co/Z2vSw3ZVc5
— Satya Mallick (@LearnOpenCV) 18 août 2023
Ever wondered how Object Keypoint Similarity (OKS) is calculated and how it manages varying scales and object sizes? Read on to know more! #computervision #AI #deeplearning #learnopencv #opencv pic.twitter.com/6NZPvJ12E4New Blog Post Alert https://
learnopencv.com/object-keypoin
t-similarity/
… Ever wondered how Object Keypoint Similarity (OKS) is calculated and how it manages varying scales and object sizes? Read on to know more! #computervision #AI #deeplearning #learnopencv #opencv -
OpenLLaMA: An Open Source Large Language Model Alternative
By
–
You might like OpenLLaMA then: https://
github.com/openlm-researc
h/open_llama
… -
Simon Willison’s Talk on LLM Developments and Challenges
By
–
Such a great talk "Catching up on the weird world of LLMs" by Simon Willison(
@simonw
). The talk is the "last few years of LLMs developments compressed in just 35 minutes". It covers a lot of things such as what LLMs are, use-cases, how they’re trained and challenges involved in -
Theory Behind Q, K, V Matrices in Language Models
By
–
Not sure whether there is any theory behind it vs just empirical observation that it works well. Maybe an intuition is that the Q, K, V matrices work well for language in general, and you don't want to screw them up. Whereas the other ones are more like the extraction params.