What Are Time Series - Applied Time Series Analysis in Python and TensorFlow

Key Takeaways

hi and welcome to the free preview of my new course applied time series analysis in python so before this course i could not find a course that covered both the statistical and deep learning approach for time series analysis if you want to learn time series analysis right now the information is very scattered you need to consult books tutorials blogs and other video courses and a lot of them will use r so that's why i made this course this course covers both the statistical and deep learning approaches all the code is in python and tensorflow so this way you have one comprehensive course to learn and master time series analysis in this free preview we will go over the basics first we'll learn what are time series and we'll see the difference between descriptive statistics and inferential statistics then we'll take a look at the statistical learning approach looking at models like the random walk moving average auto regression and the arma model which is the combination of the moving average and auto regression models now if you are interested in the full course the link will be in the description below the full course also covers more advanced models for more complex time series so we will cover of course the same as in this preview but we add on to that the arima sarima and sarimax models also var varma and varmax for multiple time series forecasting and then we move on to the deep learning section where we'll take a look at rnn's lstms auto regressive lstm cnn and residual networks to apply deep learning for time series analysis and of course we conclude the full course with an end-to-end project so again if you're interested in the course there will be a link in the description with a coupon so that you get approximately i think way more than 87 off of the regular price so of course both in the full course and this free preview it is a hands-on course so expect to code a lot you will be completing many projects both in this preview and in the full course and i am assuming that you have some background in python data science um of course deep learning not for this preview but if you are taking the full course i am assuming some deep learning experience so if you are ready let's get started let's briefly talk about what are time series a time series is simply a set of data points ordered in time therefore you can think of time as the independent variable we can divide a time series into four different components we have the level which is the average value of the time series then we have the trend which is the process that makes the values increase or decrease over time seasonality is a repeated cycle over time and finally we have noise which adds randomness to the series we will see how each component will guide us in our process of analysis and forecasting our objective in time series analysis is often to predict the future but we might be interested in understanding different components of the time series such as seasonality or if there is autoregression of course we will dive into those topics in depth later on for now let's look at some examples of time series here we see a simulated random walk meaning that your time series is completely random there is no real reason as to why it goes up or down here another example of time series where we have both an autoregressive and moving average processes in play in time we'll go over what that means and how to simulate those processes in python finally here is a real data set which is the quarterly earnings per share of the company johnson and johnson notice the trend here since it goes upward also we notice some seasonality as the values go up and down in a cyclical fashion those are are all important elements that we will learn to identify and that will impact our analysis so thank you very much for taking this free preview with me as always there is a link in the description below if you want to take the full course the link will have a promo code applied to it already so you can click on the link and you will get the course with 87 off and if by any chance you click on the link and the promo code has expired feel free to send me an email it will also be in the description and i will send you a coupon code so that you get the course on sale so thank you very much and i'll see you on the next one