Stock Market Prediction using Neural Networks for Multi-Output Regression in Python

multi-output neural networks time series regression

Neural networks can generate various outputs, which is especially useful in time-series forecasting to forecast longer periods. In time series regression, the number of neurons in the final output layer determines how many steps in a time series the model can predict. Models with one output return single-step forecasts. Models … Read more

Forecasting Beer Sales with ARIMA in Python

forecasting beer sales arima

ARIMA (Auto-Regressive Integrated Moving Average) is a statistical modeling technique for time series analysis and forecasting. Compared to machine learning, ARIMA is a classical modeling approach that is particularly powerful when the time series being analyzed follows a clear pattern. This is, for example, the case when the time series … Read more

Measuring Regression Errors with Python

measure regression errors python

Evaluating performance is a crucial step in developing regression models. Because regression models return continuous outputs, such models allow for different gradations of right or wrong. Therefore, we measure the deviation between predictions and actual values in numerical terms. However, a universal metric to measure the performance of regression models … Read more