GitHub

Neural-Network-with-Financial-Time-Series-Data

An evnet driven model that uses financial time series data with New York Times information to form a LSTM recurrent neural network. There are 3 models. The first 2 models are based on price and volume ...
Scientific Research Publishing

Koonce, B. (2021) ResNet 50. In: Koonce, B., Ed., Convolutional Neural Networks with Swift for Tensorflow. Apress, 63-72.

ABSTRACT: Background: The diagnosis and follow-up of mental disorders still rely heavily on subjective clinical assessments, highlighting the need for objective and quantitative monitoring methods.
Hosted on MSN

Backpropagation from scratch in Python – step by step neural network tutorial

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
IEEE

Comparative Analysis of CNN, RNN and LSTM for Synthetic Grip Strength Prediction

Abstract: This study assesses the effectiveness of deep learning models, specifically Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), in ...
IEEE

LSTM Hardware Inference Accelerator for LiteRT

Abstract: The efficient deployment of Recurrent Neural Networks (RNNs), particularly long short-term memory (LSTM) architectures, on edge devices has become increasingly important due to their ability ...
insideHPC

DarwinAI Generative Synthesis* Platform and Intel® Optimizations for TensorFlow* Accelerate Neural Networks

DarwinAI, a Waterloo, Canada startup creating next-generation technologies for Artificial Intelligence development, announced that the company’s Generative Synthesis platform – when used with Intel ...