Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing.
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
An Open Source Machine Learning Framework for Everyone
The official code of "CSTA: CNN-based Spatiotemporal Attention for Video Summarization"
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.
A project focusing on binary classification using Explainable Artificial Intelligence (XAI) methods, specifically SHAP (SHapley Additive exPlanations), and Grid Search for hyperparameter tuning. The project utilizes EfficientNetV2-B0 architecture on the Cat VS Dog dataset.
oneAPI Deep Neural Network Library (oneDNN)
This repository contains code and resources for my thesis project on uncertainty estimation in computed tomography (CT) scan modeling. Explore Bayesian and deterministic neural network architectures for CT analysis and compare their effectiveness in quantifying uncertainty.
A Machine Learning framework from scratch in Pure Mojo 🔥
Create automatic playlists by using Deep Learning to *listen* to the music.
A flexible, high-performance serving system for machine learning models
Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.
An Engine-Agnostic Deep Learning Framework in Java
An open source Deep Learning library for Unity.
This toolkit is a curated collection of machine learning projects, resources, and utilities designed to assist both beginners and seasoned practitioners in their journey through the fascinating world of machine learning.
Scalable and user friendly neural 🧠 forecasting algorithms.
ML-capsule is a Project for beginners and experienced data science Enthusiasts who don't have a mentor or guidance and wish to learn Machine learning. Using our repo they can learn ML, DL, and many related technologies with different real-world projects and become Interview ready.
Deep Tech R&D Research
Results of experiments with entropy regularization to reduce false positive classifications, using a toy CNN classifier for pixelated MNIST images.
Solar radiation Prediction Cameroon