The popular MNIST dataset is used for the digit recognition task using different machine learning algorithms such as KNN and SVM with HOG features. A simple feed-forward neural network is also used ...

This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanation, for ...

Diverse Domains Covered: Projects span NLP, vision, speech, and time-series. Tool-Centric Learning: Emphasis on libraries like TensorFlow, OpenCV, and Hugging Face. Practical and Scalable: Each task ...

A library of open datasets for data analytics/machine learning compiled by HackerNoon. The two most widely-used open-source machine learning frameworks for training and building deep learning models ...

Abstract: Loihi is Intel’s novel, manycore neuromorphic processor and is the first of its kind to feature a microcode-programmable learning engine that enables on-chip training of spiking neural ...

This study proposes voltage-dependent-synaptic plasticity (VDSP), a novel brain-inspired unsupervised local learning rule for the online implementation of Hebb’s plasticity mechanism on neuromorphic ...

TensorFlow is an open-source framework developed by Google scientists and engineers for numerical computing. TensorFlow.NET is a library that provides a .NET Standard binding for TensorFlow, allowing ...