Recently inflation is a popular topic in Poland and is highest since 2001. Experts presume inflation in Poland should continue to rise, and by the end of 2021 it will be close to 8%. This notebook aims to develop a forecasting model for time series using Python.

Modelos de alta dimensionalidade para previsão do IPCA

Data source: https://fred.stlouisfed.org/

LSTM neural network for inflation forecasting

Data Analytics on inflation data set using machine learning algorithms

This repository contains the code for a research on inflation prediction using different Machine Learning methods. It was developed by @estcab00 for @qlabpucp

A different way to hedge against inflation.

Group 12's 2024/25 academic year COMP5530M group project on inflation forecasting with machine learning models.

A Canada Inflation Prediction project carried out by deploying LSTM.

To address the impact of rising house prices on the economy, we built a machine learning model resistant to market trends. We experimented with Random Forest and Linear Regression models, employing sophisticated imputation methods like median state price replacement, KNN imputation, and forward/backward filling to minimize errors.

Inflation Forecasting

Modeling and forecasting inflation in Sri Lanka using ARIMA models

In this project, I extracted +40 leading indicators to forecast the UK inflation rate from Twitter tweets from 2018 to 2022 in the UK for the Data-Driven Economics course in my master's at Sapienza University

Calculations for my data-managment final project. Inflation prediction

PPTI 15 Final Project for Machine Learning Classes.

Inflation forecasting during crisis periods using Bayesian Dynamic Linear Models, traditional econometrics, and machine learning. Includes data, code, and comprehensive analysis report.

A modified Philips Curve to estimate U.S. inflation at risk using R programming. The data is imported from FRED using API.

This project was completed as the final assignment for the Fixed Income Securities Analysis and Modeling course at Zhejiang University. It employs the XGBoost algorithm to forecast future inflation rates using forward interest rates as key predictors.

I prepared a modified version of the Taylor Rule to measure inflation at risk for the U.S. economy using R programming.