It is important to learn about the Time Series forecast in Azar as it can help to predict future trends.
We have just published a course on the Frecodecamp.com on the YouTube Channel, which is introduced to the prediction of the Time Series. You will learn what the time series data is and how to break it into its key components such as trends, seasonal and remnant. Before you learn about powerful prediction techniques such as Arima and seasonal Arima, you will start making a simple baseline model. You will find out how to predict future values, evaluate your models using cross verification and add external features to improve forecasts.
The course also covers how to create prediction intervals and choose the most appropriate diagnostic matrix for your projects. You will have a clear understanding of important predictions and how to apply them in practice.
Marco Pacifico teaches this course. He is the author of the book Time series forecasts in Azigar From Manning Publications.
This video time series is the best starting point for the predictors of data. 100 % of the Code has been used to meet the basic concepts of the Time Series prediction in the course, including:
Time series data description
The timed series rotten
To predict with Arima
Cross Verification in Time Series
The use of external properties
Creating a break of forecast
Diagnosis matrix for prediction models
View the full course Freecodecamp.org YouTube channel (1.5 hours clock)