Stock-Market-Prediction-using-Numerical-and-Textual-Analysis

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

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。

Timeseries for everyone

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

Time Series Classification

Source code for predicting Blood Glucose Concentration

The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.

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

9th place solution in "Santa 2020 - The Candy Cane Contest"

ARIMA model from scratch using numpy and pandas.