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541764418's Projects

centernet

Codes for our paper "CenterNet: Keypoint Triplets for Object Detection" .

deep-forecast-pytorch

Wind Speed Prediction using LSTMs in PyTorch (https://arxiv.org/pdf/1707.08110.pdf)

deep-time-series-prediction

Seq2Seq, Bert, Transformer, WaveNet for time series prediction.

delta-free-lstm

Source code of paper "Delta-free-LSTM: An Error Distribution Free Deep Learning for Short-term Traffic Flow Forecasting"

extremenet

Bottom-up Object Detection by Grouping Extreme and Center Points

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

kmeans-anchor-boxes

k-means clustering with the Intersection over Union (IoU) metric as described in the YOLO9000 paper

lstm

Exploration of timeseries LSTM RNN prediction in pytorch, keras, tensorflow, and tensorflow.contrib.keras.

lstm_encoder_decoder

Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data

lstms_for_predictive_maintenance

LSTMS for Predictive Maintenance

pytorch-handbook

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

pytorch-yolov3

Minimal PyTorch implementation of YOLOv3

ssd.pytorch

A PyTorch Implementation of Single Shot MultiBox Detector

time-series-forecasting-of-amazon-stock-prices-using-neural-networks-lstm-and-gan-

Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.

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