Thanks to Hyosang Kim(FU Berlin), Raniyaharini Rajendran(FU Berlin) for this teamwork! Supervised learning (SL) is the machine learning task of learning a function that maps an input to an output based on example input-output pairs.[1] The majority of practical machine learning uses supervised learning. …

A time series is a dataset that tracks a sample over time and most of the articles about this series work on a specific/particular level of aggregation. But in the real world and many applications, there are multiple time series that are hierarchically organized. The related datasets have several levels…

ARIMA(p,d,q) models provide a different approach to time series forecasting, and it is a very popular statistical method form of Box-Jenkins model. Autoregressive integrated moving average can be useful in different fields like statistic to measure events that happen over a period and is also useful to predict future values…

Time is one of the most critical factor that decides whether a company will rise or not. That is why we see sales in stores or e-commerce platforms aligning with festivals. How can we analyze this kind of dataset? Time series data is a set of collection of amounts that…

Deep neural networks became one of the standard way to solve different problems like image classification, text classification, natural language processing, computer vision… A deep learning problem needs some features to be solved like loss function or optimizers. To solve, we have to define a loss function first as usual…