This project contains the analyses of a generic time series. Furthermore we analysed the main methods for forecasting time series.

Evaluation Practices done for the Time Series Forecasting subject

Time Series Analysis and Forecasting

Minimal Tensorflow time series forecasting

An exercise in analyzing, modeling, and forecasting criminal activity in Baltimore, MD using Open Source Intelligence. Coded in R.

Making a one step ahead forecast of the growth rate of the Ann Arbor, MI housing prices.

Sequence Models

Timeseries Data Prediction using Node.js

Dow Jones Index Forecasting

Contains the scripts and their results of my master thesis.

The Arctic Ice Extent Predictions project is an innovative application that uses machine learning algorithms to forecast the Arctic sea ice extent.

In this paper I will initially retrace the path marked by Ray C. Fair with his long lasting series of presidential elections forecasts exploiting the same variables he uses but enriching the model with panel data. Exploiting the Fixed Effects estimation I will then add new variables that, according to our intuition, could lead to an overall impr…

Backpropagation Neural Network for Multivariate Time Series Forecasting (multi input single output: 2 inputs and 1 output)

Working on Project related to Workforce Analytics wherein we need to understand and help the organization with its HR and workforce analytics for sustaining the business. Trying to understand the factors/ variables related to employee attrition and retention along with ensuring the business does not gets effected. Performing EDA on the features …

The project forecasts the hourly temperature at JFK airport. The dry-bulb temperature is a key indicator of air temperature that has implications for many domains, such as aviation and energy. The project involves data analysis, modeling, and validation to develop reliable forecasting model that can assist stakeholders in making informed decisions

Self-learning project