Autoencoders using Keras
A Mask R-CNN Keras implementation with Modanet annotations on the Paperdoll dataset
Identifying numbers from bankcard, based on Deep Learning with Keras
Vous trouverez ici l'ensemble du code proposé sur la chaîne Youtube L42Project
This project provides implementations with Keras/Tensorflow of some deep learning algorithms for Multivariate Time Series Forecasting: Transformers, R...
本项目利用Python的scrapy框架爬取链家网的上海市租房信息,利用pandas、numpy、matplotlib、seaborn、folium 、wordcloud 等库进行数据分析和可视化,通过one-h...
Interactive Variational Autoencoder (VAE)
Deep Learning and Machine Learning mini-projects. Current Project: Deepmind Attentive Reader (rc-data)
Tensorflow - Very Deep Convolutional Neural Networks For Raw Waveforms - https://arxiv.org/pdf/1610.00087.pdf
Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"
The word2vec-BiLSTM-CRF model for CCKS2019 Chinese clinical named entity recognition.
Learn to create & deploy a deep learning algorithm into a production REST API microservice using Python, Keras, FastAPI, & NoSQL.
Text to Image Diffusion Models in Keras
Machine Learning and Deep Learning Course
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversari...
A Deep Generative Framework for Paraphrase Generation Implementaion
Implementation of Action Recognition using 3D Convnet on UCF-101 dataset.
Keras (tensorflow) implementation of SincNet (Mirco Ravanelli, Yoshua Bengio - https://github.com/mravanelli/SincNet)
Multiclass image classification using Convolutional Neural Network
Label-Pixels is the tool for semantic segmentation of remote sensing images using Fully Convolutional Networks. Initially, it is designed for segmenti...
Implementation of CRF layer in Keras.
[ACM-CIKM] 2nd place solution at CIKM AnalytiCup 2018, a task for determining short text similarities.
Quasi-recurrent Neural Networks for Keras
An implementation for mnist center loss training and visualization
Reproducing Densely Interactive Inference Network in Keras
Package: R Interface to AutoKeras
Collection of cyber security and "AI" relevant topics
biLSTM/CNN based deep learning framework for Question Answer Selection.
VKontakte captcha bypass with pseudoCRNN model running as a chrome extension, Python, JS, 2020
Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).
Environmental sound classification with Convolutional neural networks and the UrbanSound8K dataset.
A model for short-term precipitation forecasting based on radar data
Training and deployment of deep learning models for satellite & aerial imagery
Cheatsheets on numerous topics ranging from DataScience | ML | DL | AI | Big Data.
tf.keras + tf.data with Eager Execution
CNNs for semantic segmentation using Keras library
Tutorial on how to setup your system with a NVIDIA GPU and to install Deep Learning Frameworks like TensorFlow, Darknet for YOLO, Theano, and Keras; O...
Unofficial implementation of "Max-margin Class Imbalanced Learning with Gaussian Affinity"
Integrating learning and task planning for robots with Keras, including simulation, real robot, and multiple dataset support.
[深度应用]·首届中国心电智能大赛初赛开源Baseline(基于Keras val_acc: 0.88)
📝 "End-to-end Deep Learning of Optimization Heuristics" (🥇 PACT'17 Best Paper)
Full package for applying deep learning to virtual slides.
[IEEE TGRS 2018] Spectral-Spatial Unified Networks for Hyperspectral Image Classification
Age and Sex Prediction from Image - Convolutional Neural Network with Artificial Intelligence
Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learnin...
RFCN implement based on Keras&Tensorflow
Multi-Scale Context Aggregation by Dilated Convolutions in Keras.
Tensorflow2.x implementations of CTR(LR、FM、FFM)
Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.
Tool to evaluate deep-learning detection and segmentation models, and to create datasets