Continuing my machine-learning series—this time on unsupervised learning. The post walks through cleaning ingredients, building vectors, choosing K, clustering, and retrieving similar dishes.

https://agingcoder.com/posts/2025-08-25-clustering-the-cookbook-a-taste-of-unsupervised-learning/

#MachineLearning #UnsupervisedLearning #Python

#Zoomposium with Dr. #Patrick #Krauß: “Instructions for building #artificialconsciousness”

Translating the various stages of #Damasio #theoryofconsciousness 1:1 into concrete #circuitdiagrams for #deeplearning. To this end, strategies such as #feedforwardconnections and #recurrentconnections in the form of #reinforcementlearning and #unsupervisedlearning are used to simulate the #biologicalprocesses of #neuralnetworks.

More at: https://philosophies.de/index.php/2023/10/24/bauanleitung-kuenstliches-bewusstsein/

or: https://open.spotify.com/episode/0httDEYGoUGxJ6lHA03LEZ?si=BzmZn3EvQr6imSzUUKG8RQ

#PatrickKrauß #PatrickKrauss #Zoomposium #ArtificialIntelligence #Consciousness #DeepLearning #Neuroscience #Damasio #ArtificialConsciousness #NeuroscienceInspiredAI #CognitiveNeuroscience #Embodiment #TuringTest #AI #ArtificialConsciousness #Ethics #AIrisks #MachineConsciousness #ComputationalNeuroscience #ReinforcementLearning #UnsupervisedLearning #CognitiveComputing #ArtificialGeneralIntelligence #PhilosophyOfMind #BlackBoxProblem #ExplainableAI #Neuroinformatics #DigitalMind #FutureOfAI

#Zoomposium mit Dr. #Patrick #Krauß: „Anleitung zum Aufbau von #KünstlichemBewusstsein”

Übersetzung der verschiedenen Stufen von #Damasio #Bewusstseinstheorie 1:1 in konkrete #Schaltpläne für #DeepLearning. Zu diesem Zweck werden Strategien wie #Feedforward-Verbindungen und #rekurrenteVerbindungen in Form von #Verstärkungslernen und #unüberwachtemLernen verwendet, um die #biologischenProzesse von #neuronalenNetzwerken zu simulieren.

Mehr auf: https://philosophies.de/index.php/2023/10/24/bauanleitung-kuenstliches-bewusstsein/

oder: https://open.spotify.com/episode/0httDEYGoUGxJ6lHA03LEZ?si=BzmZn3EvQr6imSzUUKG8RQ

#PatrickKrauß #PatrickKrauss #Zoomposium #KünstlicheIntelligenz #Bewusstsein #DeepLearning #Neurowissenschaften #Damasio #ArtificialConsciousness #NeuroscienceInspiredAI #KognitiveNeurowissenschaft #Embodiment #TuringTest #KI #KünstlichesBewusstsein #Ethik #KIrisiken #MachineConsciousness #ComputationalNeuroscience #ReinforcementLearning #UnsupervisedLearning #CognitiveComputing #ArtificialGeneralIntelligence #PhilosophieDesGeistes #BlackBoxProblem #ExplainableAI #Neuroinformatik #DigitalMind #FutureOfAI

Don't pass by the new insightful lecture from Dr. Alejandro Rodriguez Garcia, Abdus Salam International Centre for Theoretical Physics (ICTP)!

In this one, Alex provides a comprehensive overview of various clustering methods, including flat, fuzzy, and hierarchical approaches. His lecture not only discusses the mathematical foundations of techniques like k-means and k-medoids but also highlights their practical applications across fields such as image recognition and data classification.

This lecture is an excellent opportunity to deepen your understanding of unsupervised learning and engage critically with advanced clustering methods.

Join Enabla to watch the lecture and interact with Dr. Rodriguez Garcia for free! Ask questions and spark discussions with both him and the rest of the Enabla community: https://enabla.com/pub/1109/about

#UnsupervisedLearning #MachineLearning #DataScience #Clustering #OpenAccess

We are excited to welcome Prof. Alejandro Rodriguez Garcia from the Abdus Salam International Centre for Theoretical Physics (ICTP) to Enabla! In his lecture, Alex continues the topic started by Marcello and explores the use of unsupervised machine learning techniques in many-body quantum systems, highlighting how dimensionality reduction can illuminate structure within complex data. Particular emphasis is placed on the Principal Component Analysis (PCA) as a key method to maximize variance while reducing dimensionality. This lecture sets the stage for future topics such as clustering and manifold learning.

🎥 Join us for this #OpenAccess lecture and take advantage of Enabla's unique features to ask questions directly to Prof. Rodriguez Garcia and engage in discussions with the community: https://enabla.com/pub/1112/about

Don't miss this opportunity to enhance your knowledge in the intersection of data mining and quantum physics!

#MachineLearning #UnsupervisedLearning #DimensionalityReduction #QuantumSystems #PCA #DataMining #OpenScience

I put up an essay on my blog: "Unsupervised AI Children". It's about the issue of unsupervised AI doing self-directed learning.

https://netsettlement.blogspot.com/2025/05/unsupervised-ai-children.html

#AI #learning #unsupervised #UnsupervisedLearning #LLM #LLMs #ethics #AIEthics #safety #technology #risk #AlphaEvolve #MachineLearning #EvolutionaryProgramming

We are pleased to announce a second lecture from Dr. Marcello Dalmonte (ICTP) on the intricacies of statistical mechanics and phase transitions in the context of data mining the many-body problem. In this part, Marcello discusses essential concepts of the partition function, emphasizing efficient sampling strategies via Markov chains and Monte Carlo simulations. He specifically addresses the challenge of critical slowing down near phase transitions and introduces cluster algorithms as a powerful tool for effective sampling at criticality. Using the illustrative example of a three-site Ising model, Dr. Dalmonte demonstrates how temperature impacts the intrinsic dimensionality of feature spaces, providing valuable insights into many-body systems.

🎥 Don't miss this #OpenAccess opportunity to watch the lecture for free and engage in discussions with the Enabla community, including Marcello himself: https://enabla.com/pub/325/about

The first lecture of the same series was announced earlier: https://mathstodon.xyz/@enabla/113163357376577315

#StatisticalMechanics #UnsupervisedLearning #machine_learning #MonteCarlo #PhaseTransitions #IsingModel #OpenScience