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Let's understand autocorrelation function also called as ACF and partial autocorrelation function P ACF in this one very clearly, we will understand the importance of it, why it matters, and also the math behind it very clearly, right. Complete Machine Learning Course for FREE: https://rb.gy/posrbk Checkout complete Data Scientist Learning Path here: https://edu.machinelearningplus.com/s... 🔹 Introduction to Time Series Modeling - ACF and PACF (2022) Now, say you have a time series you have that date and your value this data forms your time series right. In many of the times these that you will see in the real world, you will find that the previous values of the same series can be helpful to predict its future values. So, suppose this is d one D two these are the days or the time points in your series and the values are right as 12345 for the sake of simplicity, I will write like this. And we also have the lags of the series lag one, lag, two of y and so on. computing the legs also parallely. So, this will be this will be hash, this is 123, and so on. You have the series and its legs. Now, what I'm saying is, if you have if you want to predict or model this series based on his like you will write the equation something like this, the Y is dependent on its lags itself, lag one off y lag, two off y and so on as many lines as you want, we don't know how many lags it is dependent on we will keep this we will not build this up. But this is an idea right? The current value of y is explained by its past values. So to predict what this value will be, we know the value of the land at this point this will be five lakh one of lag one of y at these six. Let me know in the comments section if you have any questions! 🤝 Like, Share, Subscribe for more! Follow us on our social media handles for all updates, events and live sessions- ✅ Instagram: / machinelearningplus ✅ LinkedIn: / machine-learning-plus ✅ YouTube: / numyard ✅ Twitter: / r_programming ✅ Website: https://www.machinelearningplus.com/ If you enjoyed this video, be sure to throw it a like and make sure to subscribe to not miss any future videos! Thanks for watching! #machinelearningplus #python #machinelearning #datascience