Time Series In R | Time Series Forecasting | Time Series Analysis | Data Science Training | Edureka
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In this Edureka tutorial we will show you how to use the Time Series Analysis in R to predict the future! Below are the topics we will cover in this tutorial: 1. Why Time Series Analysis? 2. What is Time Series Analysis? 3. When Not to use Time Series Analysis? 4. Components of Time Series Algorithm 5. Demo on Time Series
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Time Series In R | Time Series Forecasting | Time Series Analysis | Data Science Training | Edureka
- 1. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Agenda What Is Artificial Intelligence ? What Is Machine Learning ? Limitations Of Machine Learning Deep Learning To The Rescue What Is Deep Learning ? Deep Learning Applications
- 2. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Agenda Why Time Series Analysis? What is Time Series Analysis? When not to use Time Series? Components of Time Series Algorithm Demo
- 3. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Why Time Series Analysis?
- 4. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Why Time Series Analysis? Comparing to other forecast algorithms, like logistic regression or linear, they deal with two variables, But with time series we deal a single variable which is dependent on time.
- 5. Copyright © 2017, edureka and/or its affiliates. All rights reserved. What is Time Series Analysis?
- 6. Copyright © 2017, edureka and/or its affiliates. All rights reserved. What is Time Series Analysis? A time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Time series forecasting is the use of a model to predict future values based on previously observed values.
- 7. Copyright © 2017, edureka and/or its affiliates. All rights reserved. When Not To Use Time Series Analysis?
- 8. Copyright © 2017, edureka and/or its affiliates. All rights reserved. When Not To Use Time Series Analysis? • When Values are constant.
- 9. Copyright © 2017, edureka and/or its affiliates. All rights reserved. When Not To Use Time Series Analysis? • When Values can be represented using known functions such as sin x.
- 10. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Components Of Time Series
- 11. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Components Of Time Series A general direction in which something is developing or changing. General Trend Seasonal Irregular Fluctuations
- 12. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Components Of Time Series General Trend Seasonal Irregular Fluctuations A peak or dip which is seen in a time interval
- 13. Copyright © 2017, edureka and/or its affiliates. All rights reserved. Components Of Time Series General Trend Seasonal Irregular Fluctuations The uncontrolled situations which arise due to which the value changes
- 14. Copyright © 2017, edureka and/or its affiliates. All rights reserved. WebDriver vs. IDE vs. RC ➢ Data Warehouse is like a relational database designed for analytical needs. ➢ It functions on the basis of OLAP (Online Analytical Processing). ➢ It is a central location where consolidated data from multiple locations (databases) are stored.