Mind blowing indeed! Seeing the sklearn classification_report parameters makes me wonder whether its the output of generation or Memoization.
MACHINE LEARNING
-
Overtraining Neural Networks for Memorizing Transformations
By
–
I think we can always overtrain a neural net to memorise this transformation!
-
Artificial Intelligence Saves Stroke Victims Using Deep Learning
By
–
Medical Moment: Using artificial intelligence to save stroke victims – WNDU Read more here: https://
ift.tt/Ikmc2V3 #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
ChatGPT likely derived from Codex via text-davinci-002 model lineage
By
–
ChatGPT’s model is likely descended from Codex. Models are developed off of other models. The model ChatGPT uses was probably based on another model called text‑davinci‑002, which is based on code‑davinci‑002, a Codex model. So it was trained on code at one point.
-
AI Advances Cancer and Muscle Research at Columbia
By
–
Artificial intelligence changing the game in MU cancer, muscle research – Columbia Missourian Read more here: https://
ift.tt/zL62ORt #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
Favorite MLOps and hosted ML tools discussion
By
–
What are your favorite MLOps tools or hosted ML tools, and why?
-

Comprehensive Guide to Machine Learning Free Book
By
–
Free Book: A Comprehensive Guide to #MachineLearning http://
bit.ly/2AAidka #AI #NeuralNetworks #TensorFlow #Algorithms #Programming #Python #ML #100DaysOfCode #javascript #linux #cloud #serverless #BigData #Analytics #womenwhocode #devcommunity #DataScience #DeepLearning -

World Models and Reinforcement Learning in Control Theory
By
–
Agree with the last one, but we still work on a lot of reinforcement learning, because our world models are not present/perfect. @SahinLale is working at the intersection of learning and control. Check out his work for excellent theoretical background as well as empirical results
-

Generative AI Essential for Concept Learning Beyond Art Creation
By
–
Strongly disagree with the first one. "What I cannot create I cannot understand" – Richard Feynman. Generative AI is not just for creating fun art, it is at the core of concept learning.
-
Learning and Refining Semantic Categories from Single Instances
By
–
Learn a word based on a single instance (e.g. this particular airplane = word "airplane"), then use the word to refer to a broad category of related things (all flying things are now airplanes), then gradually refine semantic categories (helicopters, dirigibles…)