Bangladesh-Weather-Forecasting-using-Time-Series-and-Deep-Learning-Models

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models

Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs

Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.

Timeseries for everyone

next version move to https://github.com/billchen198318/hillfog, bambooBSC is an opensource Balanced Scorecard (BSC) Business Intelligence (BI) Web platform. BSC's Vision, Perspectives, Objectives of strategy, Key Performance Indicators (KPIs), Strategy Map, and SWOT, PDCA & PDCA report, Time Series Analysis.

Source codes and corpora of paper "Iterated Dilated Convolutions for Chinese Word Segmentation"

reference tensorflow code for named entity tagging