Time Series Forecasting in Minutes | Time Series Analysis Overview

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In this data science in minutes, we will describe what time series forecasting is, and provide several examples of when you can use time series for your data. Time series forecasting is looking at data over time to forecast or predict what will happen in the next time period, based on patterns or re-occurring trends of previous time periods.

0:00 – Introduction
0:25 – Seasonal Sales
1:15 – Time series example
2:17 – Conclusion

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  1. Data Science Dojo
  2. time series analysis
  3. time series forecasting
  4. time series
  5. data prediction
  6. time series data
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Комментарии
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Good and clear introduction to this topic, thanks for your time invested on this video.

thazapo
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Great insight, I tend to think of time series only as financial series but this introduction shows that there are lots of applications.

clerisduchrist
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how do we deal with the holidays such as July 4. you will receive no calls. Please advise asap. Thanks

hammadsafdar
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I'm looking for an exact equation for "Linear Regression Extrapolation on Time-series spatial data". can anyone help me?

tamalsaha
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I just wanna say that this time series forecasting uses inductive reasoning which is NOT always correct. Inductive reasoning will not always yield truthful results.

For instance:
Just because it rained yesterday doesn't mean it will rain today. Just because it was sunny today doesn't mean it will be sunny tomorrow.

However, if A is the union of B and C and D is the union of E and F...and B=E and C=F then by transitivity, A=D.
^That is deductive.

With the principle of mathematical induction you can prove certain things to be true inductively, however certain requirements must be upheld in order to use this proof method.

Furthermore, there are many, many times when deductive reasoning is a more effective way of determining the surety of an occurrence than inductive reasoning.



It depends on the context entirely.

kagayakuangel