The aim of this repository is to create RBMs, EBMs and DBNs in generalized manner, so as to allow modification and variation in model types.
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Updated
Sep 22, 2024 - Python
The aim of this repository is to create RBMs, EBMs and DBNs in generalized manner, so as to allow modification and variation in model types.
Generative Adversarial Networks in Pytorch and Tensorflow
Train and sample Restricted Boltzmann machines in Julia
.NET Standard SDK to send messages with CM.com
Neural network ansatz to approximate a ground state by using variational Monte Carlo (VMC)
Javascript SDK to send messages with CM.com
Demonstration of the Mode-Assisted Quantum-RBM as Python Class (PyTorch based) on an image classification task.
Millions of businesses rely on SMS to communicate with mobile consumers. Credit card fraud alerts, flight status updates, and package delivery notifications are common examples of business-to-consumer SMS. RCS (Rich Communication Services) upgrades SMS with branding, rich media, interactivity and analytics. With RCS, businesses can bring branded…
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Utilisation de modèles génératifs comme tâche prétexte pour pré-entrainement de DNN pour classification.
A Python-implemented RBM project exploring generative learning through the classification of the Iris dataset, featuring a user-friendly GUI and advanced data handling capabilities.
Fast Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)
👻 Extend your WooCommerce store capabilities. Send personalized bulk SMS messages. Notify your customers about order status via customer SMS notifications. Receive order updates via Admin SMS notifications.
A command line operated Movie Recommender system that recommends unwatched movies for a user using their existing MovieLens movie ratings as input. The algorithm uses two KNN algorithms for collaborative filtering and an Explainable-RBM with two visible dimensions to predict user ratings for unwatched movies.
Deep Belief Networks in Tensorflow 2
A series of 12 assignments/labs regarding Stochastic Processes and Machine Learning including a plethora of models and techniques implemented in Google Colab notebooks
Machine Learning Library, written in J
Hands-on in-person workshop for Deep Learning with TensorFlow
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