Quantum Neural Networks
[..]QNNs promise to overcome limitations inherent in classical computing, offering transformative potential across various domains such as cryptography, optimization, drug discovery, and artificial intelligence[..]
If you are skeptical about LLMs and LRMs, this is a post for you. Written by a guy that has seen some things wrt technology and machine learning
This project aims to analyze and visualize crime data in Bucharest using geospatial mapping and machine learning techniques. The primary focus is on classifying crime severity and making predictions about...
Handling Missing Data in Machine Learning
Missing data is a common issue in machine learning that can significantly impact the performance of models if not handled properly. Missing data can occur due to various reasons, such as data entry errors, equipment malfunctions, or non-responses in surveys. The way missing data is managed can influence the accuracy, efficiency, and robustness of machine learning models.
If you missed it, get a chance to yourself, have the book, and leave feedback.
https://www.goodreads.com/book/show/236252020-artificial-intelligence-neural-networks-and-privacy
#AI, #artificialintelligence #DataProtection #privacy #NeuralNetworks
Optimizing Neural Networks
Optimizing neural networks involves improving how the model learns, generalizes, and operates under different conditions. This article offers a detailed exploration of the key techniques for optimizing neural networks, from...
In this project, we create a miniature version of a Large Language Model (LLM) using Python. The goal is to build a conversational AI that can answer user questions based on a predefined knowledge base stored in a JSON file.
#NeuralNetworks pre-trained with #RetinalWaves, spontaneous activity in the early #VisualSystem, predict motion faster and more accurately. Julijana Gjorgjieva and her team showed this phenomenon in simulations and real-world scenes: http://go.tum.de/361879
@ERC_Research 
A.Eckert
Horovod is an open-source library designed for distributed training of deep learning models across multiple GPUs and nodes. It is framework-agnostic and integrates seamlessly with popular machine learning libraries such as TensorFlow, PyTorch, Keras...
Machine Learning Libraries: TensorFlow, PyTorch & scikit-learn
[..]behind every successful machine learning model lies a robust library or framework that simplifies the process of building, training, and deploying[..]
I thoroughly enjoyed Antonio Somaini’s lecture tonight on the Politics of Latent Spaces at the conference Art in the Age of Average. The new AI-thoritarians.
His reflections on compression as a cultural and epistemic process were truly inspiring — and the sources cited were excellent, too ;)
#AI #LatentSpaces #DigitalCulture #Compression #Vectorization #NeuralNetworks #ArtAndAI #MachineVision #epistemiccompression #AIAesthetics @databasecultures
My new book is out today — in Italian:
“Intelligenza Artificiale, Privacy e Reti Neurali: L’equilibrio tra innovazione, conoscenza ed etica nell’era digitale”
With Forewords by Danilo Mandic and Carlo Morabito, and an introduction by Guido Scorza.
The English edition will be available soon.
Now available on all major online bookstores.
Fresh New Article: 'How Can Machine Learning Accelerate Drug Discovery and Healthcare Research?'
Read here:
https://ml-nn.eu/a1/85.html
https://rackenzik.com/top-7-advances-in-3d-reconstruction/
#3DReconstruction #ComputerVision #DeepLearning #ArtificialIntelligence #AI #NeuralNetworks
#NeRF #NeuralRadianceFields #3DGaussianSplatting #Photogrammetry #StructuredLight
#MachineLearning #VisionAI #ARVR #Robotics #AutonomousVehicles
#MedicalImaging #HealthcareAI #DigitalHeritage #VirtualEnvironments
#OpenScience #TechForGood #AIFuture #Innovation #Research
An enhanced mineral identification model, YOLOv8-SBI, based on an improved YOLOv8 framework, was introduced, improving the precision of mineral feature detection. #OpenAccess at https://www.sciencedirect.com/science/article/pii/S2352854025000166 #ArtificialIntelligence #DeepLearning #NeuralNetworks #Mineralidentification
Dynamic Pricing with Machine Learning
Dynamic pricing refers to the practice of adjusting product or service prices in response to changing conditions. This could include shifts in demand, customer behavior, market trends, or even the time of day. While the concept has existed for decades—most notably in the airline and hospitality sectors—machine learning has brought a new level of precision and scale to...
