Forcast-euro-yen

Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets

Timeseries for everyone

基于ARIMA时间序列的销量预测模型，实际预测准确率达90%以上，内含有测试记录和实际上线效果。

Time Series Classification

Photovoltaic power prediction based on weather data for my bachelor thesis

Source code for predicting Blood Glucose Concentration

PyTorch tutorial for using RNN and Encoder-Decoder RNN for time series forecasting

Time Series forecasting using Seasonal ARIMA & Prophet. Applied statistical tests like Augmented Dickey–Fuller test to check stationary of series. Checked ACF ,PACF plots to identify Moving average and Auto-regressive order of series. Transformed series to make it stationary.

In this project we will be looking at data from the stock market, particularly some technology stocks. We will learn how to use pandas to get stock information, visualize different aspects of it, and finally we will look at a few ways of analyzing the risk of a stock, based on its previous performance history.

My Solution to the Assignment Task based on Telecom Italia's Big Data Challenge