Excel-vba 开发使用手册

Time series Forecasting of Wind speed based on different deep learning methods LSTM - GRU

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs

Creating real-time dynamic Point Clouds using PyQtGraph, Kinect 2 and the python library PyKinect2.

capture videos from kinect v2 with QT