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Extracting relevant information from resume using deep learning.

Sparse Recurrent Neural Networks -- Pruning Connections and Hidden Sizes (TensorFlow)

由时间空间成对组成的轨迹序列，通过循环神经网络lstm，自编码器auto-encode，时空密度聚类st-dbscan做异常检测

(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset

该工程基于Python3.6，tensorflow1.6。主要是对tensorflow框架进行认识，实践和应用，快速掌握tf在深度学习上的使用，包括线性模型，minist数据集分类，Tensorboard，CNN，LSTM，图像识别网络inception-v3，多任务学习以及验证码识别， word2vec，语音分类模型等实践。配合https://www.bilibili.com/video/av20542427 视频学习更佳。要求在一定的机器学习或深度学习的基础（更新中）

LSTM neural networks for nowcasting economic data.

A model for short-term precipitation forecasting based on radar data

A project using deep learning to forecast stock prices and covariance. Uses multiple threads to gather data and optimize portfolio using numerous APIs.

[IEEE TGRS 2018] Spectral-Spatial Unified Networks for Hyperspectral Image Classification

集成各种神经网络进行情感分类，包括CNN、LSTM、Transformer以及BERT等网络模型