libs.garden
Most popular libraries and apps
Categories
Deep Learning
facebookresearch/dlrm β An implementation of a deep learning recommen...
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An implementation of a deep learning recommendation model (DLRM)
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facebookresearch/dlrm
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Next-item recommendation on top of Amasonβs explicit rating dataset, using deep learning with Keras
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iritfh1/Next-item-recommendation-using-keras
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Our Deep Learning Model will predict which user is going to like which movie using the recommendation system using Boltzmann Machine
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kaushik1094/Movie-Recommendation-System
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Contains code which covers various methods for recommending movies, some of the methods include matrix factorisation , deep learning based recommendation systems
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Gurupradeep/Movie-Recommendation-System
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Deep Learning Project for Playlist Recommendation based on a User's current session
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klaidas/Deep-Learning-Playlist-Recommendation
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Movie Recommendation System by Deep Learning
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yuqiw4/Movie-Recommendation-System-by-Deep-Learning
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Music Recommendation System with Deep Learning Methods and Big Data Analytics
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Sapphirine/Music-Recommendation-System
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This repository contains articles, papers and repositories on deep learning based recommendation system
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liushangnihao/Deep-learning-based-recommendation-system
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Milestone/Inspiring paper for deep learning practitioner.
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Joker316701882/DL-Paper-Recommendation
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Winning solution for hackerearth's deep learning #4 challenge
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kunwar31/hackerearth-tag-recommendation
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A recommendation engine that uses supervised learning techniques to predict userβs future trips on the basis of their past trips and preferences. Uses Microsoft Azure to implement machine learning techniques to create a user-specific profile. The recommendation system is built on deep learning (neural networks with backpropagation). The neural network was trained to recommend house listings which coincided with the userβs traits. It is a Spring MVC application using MongoDB and Morphia. 1.3 million listings and user data were stored in MongoDB. The listings that were recommended to the users were fed into MongoDB and were displayed in the application using Google Maps API. Being a frequent Airbnb user myself, my wish for a more personalized experience for planning my future Airbnb trips inspired the concept behind this project.
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neeleshsaxena/Profile-Based-Recommendation-Engine
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"Introduction to Deep Learning: Theory and Implementation Based on Python" is a Great Book !!!
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XWHQSJ/Deep-Learning-Theory-and-Implementation-Based-on-Python
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Deep Learning has emerged as a new area in machine learning and is applied to a number of image applications. The main purpose of the this work is to apply the concept of a Deep Learning algorithm namely, Convolutional neural networks (CNN) in image classification. The algorithm is tested on standard COCO datasets. The performance of the algorithm is evaluated based on the quality metric known as Mean Squared Error (MSE) and classification accuracy. The experimental result analysis based on the quality metrics and the graphical representation proves that the algorithm (CNN) gives fairly good classification accuracy for all the tested datasets. Then we used visualization technique on the particular image for understanding which part of a given image led to convert to its final classification decision. For this we used CAM Visualisation technique. We also tried in doing object detection by using Pytorch.
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LeadingIndiaAI/-DESIGN-AND-IMPLEMENTATION-OF-PROCESSING-MODULE-FOR-OBJECT-DETECTION-AND-WEAPON-CLASSIFICATION-WITH-
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Face recognition, computer vision, deep learning, PYNQ, Movidius NCS
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666DZY666/Design-and-Implementation-of-Face-Recognition-based-on-PYNQ
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This repository provides tutorial code for deep learning researchers to learn PyTorch.
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rollno55044/PYTORCH---implementation-of-models-in-pytorch-framework
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Implementations of (Deep Learning + Machine Learning) Algorithms
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adityashrm21/Deep-Learning-Algorithms-Implementation
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Implementation for CVPR 2015 Paper: "An Improved Deep Learning Architecture for Person Re-Identification".
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Ning-Ding/Implementation-CVPR2015-CNN-for-ReID
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BiDAF: Question Answering models in NLP is an intriguing field but there are many challenges before we a model can reach human level comprehension. This is my first attempt at exploring how to implement a Reading Comprehension model using Pytorch deep learning framework.
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aparajita15/BiDAF-implementation
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Implementation of machine learning and deep learning technique
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yedam-Lee/ML-implementation
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DeepID-implementation is an implementation of paper "Deep Learning Face Representation from Predicting 10,000 Classes"
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joyhuang9473/deepid-implementation
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Do you wonder how to implement algos in the papers you are reading and the implementations on GitHub are hard to modify? This repository will demonstrate how to make deep learning algos implementations in a really obviously way.
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tzattack/Project-Implementation
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Deep learning model for predicting personality traits based on facial features.
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adessoAG/facenality-model
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Use deep learning to learn a turbulence model from high fedelity data. The model can reasonably predict other turbulent flows.
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fyang235/Deep-Learning-Turbulence-model
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An experimental deep learning library
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kahnvex/slugnet
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DL(Deep Learning) beginners to deploy NVIDIA GPU accelerated platform in an instant.
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Sniper711/DL-Beginners-NVIDIA-GPU-accelerated-Platform-in-an-instant
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An advanced deep learning approach using Semantic Segmentation to assign each pixel of an image to an object using inferences to have real time detection
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Jeremy26/semantic-segmentation
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An embedded deep learning library for Go.
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therfoo/therfoo
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An universal deep learning models conversor
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edgarriba/DeepRosetta
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an open framework for deep learning
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1icas/BigBang
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An image database for deep learning.
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aaalgo/picpac
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