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 in a series. What are the components of this model?

Let’s see the definition of AR, I, and MA.

Figure 1 Time series visualization

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 put together at equal time slots and ordered. Therefore, it is a sequence of discrete-time data. For example, a monthly number of sold fruits…

Figure Example for time series

A multivariate time series has more than one time dependent variable(time series). Each variable depends not only on its past values but also has some relation…

Deep neural networks became one of the standard way to solve different problems like image classification, text classification, natural language processing, computer vision…

Figure 1 Image classification example 1

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. After this operation, the optimization algorithm is ready to minimize the loss function. Let’s continue with the optimization part.

Ceyda Akbulut

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