superrichiesui Goto Github PK

deep_learning

About this Specialization The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. In this Specialization, you will build neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. You will master these theoretical concepts and their industry applications using Python and TensorFlow. You will tackle real-world case studies such as autonomous driving, sign language reading, music generation, computer vision, speech recognition, and natural language processing. AI is transforming many industries. The Deep Learning Specialization provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI. Along the way, you will get career advice from deep learning experts from industry and academia.

deep_metric_learning_tf2.0

A tensorflow2.0 implementation of triplet loss with online hard mining strategy

deep_sort_yolov3

Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow

deeprec

Implementation of Deep Learning based Recommender Algorithms with Tensorflow.

deepresearch

This repository is the collection of research papers in Deep learning, computer vision and NLP.

deepspeech

A TensorFlow implementation of Baidu's DeepSpeech architecture

deepspeechrecognition

A Chinese Deep Speech Recognition System 包括基于深度学习的声学模型和基于深度学习的语言模型

deepwaldo

Using MaskRCNN to solve Where's waldo

demo-fastbert-multi-label-classification

densenet-base-mask-rcnn-for-human-pose-estimation

densepose

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

densepose-video

Code to run densepose on video with detectron. https://github.com/facebookresearch/Detectron

densepose-webcam

densesqueeze-rcnn

Optimized implementation of DensePose RCNN

dface

Deep learning face detection and recognition, implemented by pytorch. (pytorch实现的人脸检测和人脸识别)

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dialog_corpus

用于训练中英文对话系统的语料库 Datasets for Training Chatbot System

diffusion-models-papers-survey-taxonomy

Diffusion model papers, survey, and taxonomy

dkn

A tensorflow implementation of DKN (Deep Knowledge-aware Network for News Recommendation)

dlib

A toolkit for making real world machine learning and data analysis applications in C++

dlib-models

Trained model files for dlib example programs.

dlrm

An implementation of a deep learning recommendation model (DLRM)

dmcp

doc-han-att

Hierarchical Attention Networks for Chinese Sentiment Classification

doccano

Open source text annotation tool for machine learning practitioner.

docker-ubuntu-vnc-desktop

Docker image to provide HTML5 VNC interface to access Ubuntu LXDE and LXQT desktop environment

docx-mailmerge

Mail merge for Office Open XML (docx) files without the need for Microsoft Office Word.

dog-breed-classifier-using-tf2.0

A simple classification model takes the advantage of transfer learning to train the model to identify the dog images.

dogs-cats

猫狗二分类图片识别

dogsvscats

图像二分类问题 猫狗大战 pytorch CNN