A Repo of Time-series analysis techniques. Holt-Winter methods, ACF/PACF, MA, AR, ARMA, ARIMA, SARIMA, SARIMAX, VAR, VARMA, RNN Keras, Facebook- Prophet etc.

This repo uses Natural Langauage Processing, time series analysis, and ARIMA to explore predictive housing trend analysis.

Machine Learnings Application on Airquality datsets. Implemented many analytical models on air quality dataset and compared them on the basis of mean squared error , root mean squared error, mean absolute error and and Accuracy.

Build a forecasting model to predict the sale of a store.

A Simple Python Implementation of an API that provides services like Classification,Regression and Forecasting on the input data set

A neural network model for predicting cryptocurrency prices using machine learning and time series analysis techniques.

Predicted Volatility: Applying Predicted Volatility to Determine Profitability of Cyclical and Defensive ETFs

This repository covers essential techniques for time series analysis and forecasting. It covers data manipulation and visualization using Numpy and Pandas, time series analysis with Statsmodels, ARIMA models, deep learning methods like RNNs, LSTM, GRU, etc. and Facebook's Prophet library.

Applying time series techniques to the US macroeconomics dataset. This repository is based on the Applied Time Series Analysis in Python course by Marco Peixeiro on Udemy.