Collaborative and hybrid recommendation systems
-
Updated
Oct 22, 2024 - Jupyter Notebook
Collaborative and hybrid recommendation systems
Basil is a master detective, excellent at spotting inconsistencies and uncovering hidden clues. Think Anamoly Detection.
DocEnTr: An end-to-end document image enhancement transformer - ICPR 2022
Explore Network Anomaly Detection Project 📊💻. It achieves an exceptional 99.7% accuracy through a blend of supervised and unsupervised learning, extensive feature selection, and model experimentation. Stunning data visualizations using synthetic network traffic data offer insightful representations of anomalies, enhancing network security.
Multiple Sclerosis Detection using 3D Auto-Encoders for volumetric MRI scans
Various Deep Learning Projects (2022- 2023)
Research on Material Science using Neural Networks black box approach
PyTorch implementation for the framework presented in the paper: Generative Fourier-based Auto-Encoders: Preliminary Results paper
Implemented K-Means Clustering from scratch on Cifar-10 dataset, Optimized the model using Auto- Encoders.
Deep Learning Computer Vision Algorithms for Real-World Use
My research work with a proof of concept for Image Restoration of motion-blurred images in Real-time using data augmentation and specific architecture of Deep Autoencoder network (inspired from U-Net model) with CNN layers. (Studied extensive use of functional APIs for custom layers, loss, and metrics, effects of regularization & Hyperparams opt…
PyTorch Blog Post On Image Similarity Search
Building Auto-encoders using Deep Learning models in PyTorch
In this repository, denoising of medical images has been performed using convolutional auto-encoder models.
Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.
simple VAE pytorch implementation
Auto encoders based recommendation system
A docker environment and notebooks to experiment with the extraction of moore machines from RNN RL policies
Implementation of some famous machine learning algorithm from scratch
Add a description, image, and links to the auto-encoders topic page so that developers can more easily learn about it.
To associate your repository with the auto-encoders topic, visit your repo's landing page and select "manage topics."