Penny Liang: Understanding Large Models for Humanities Students (1.0)

Penny Liang's book, "Understanding Large Models for Humanities Students (1.0)," explains the core technologies of large models from a simplified perspective. It breaks down complex concepts from the ...
Hosted on MSN

Neural Network python from scratch | MultiClass Classification with Softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
IEEE

Skew Logistic Distribution Applied as Activation Function in Artificial Neural Networks

Abstract: In recent years, Artificial Neural Networks (ANNs) have stood out among machine learning algorithms in many applications, such as image and video pattern recognition. Activation functions ...
Frontiers

Automated classification of midpalatal suture maturation using 2D convolutional neural networks on CBCT scans

School of Dentistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada Introduction: Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, ...
Scientific Research Publishing

Leshno, M., Lin, V.Y., Pinkus, A. and Schocken, S. (1993) Multilayer Feedforward Networks with a Nonpolynomial Activation Function Can Approximate Any Function. Neural Networks ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
Hosted on MSN

What Is An Activation Function In A Neural Network? (Types Explained Simply)

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! #NeuralNetworks ...
IEEE

ASTRA: Reconfigurable Training Architecture Design for Nonlinear Softmax and Activation Functions in Transformers

Abstract: The efficient training of Transformer-based neural networks on resource-constrained personal devices is attracting continuous attention due to domain adaptions and privacy concerns. However, ...