Time Series Next Steps Video Lecture Transcript
This transcript was automatically generated, so there may be discrepancies between the video and the text.

Hi, everybody. Welcome back in this video. We'll wrap up our time series videos by talking about the next steps you might want to take if you're interested in learning more about time series analysis and forecasting. ... So in this section, we've focused on some of the most basic concepts including how do you adjust data splits for time series data.
Uh What are some baseline models uh as well as what are some of the uh more common models people will apply to their time series forecasts while we do present additional content uh that expands upon this in both the problem sessions and practice problems. Notebook, you may wish to get more detailed information on the subject of time series analysis and forecasting.
So two more theoretical books that you may be interested in. What do I mean by theoretical? I mean they cover more of the statistical background involved in time series analysis are the analysis of Time series by Chris Chatfield and the uh Time Series analysis and its applications by Robert H Shumway and David S Stouffer. So both of these links will take you to uh where you can find more about these books Uh And if you're interested, I encourage you to read them.
Uh I especially found this first one very readable, um easy to read and understand. As for Python packages, we exclusively use stats models T S A module which is linked to here. Uh So this was for exponential smoothing hat winter uh auto correlation plots. Um As well as a. Uh we use these in these notes. Uh We also use, we did also use K learns uh cross validation for time series.
Um And uh at least you could use it. We didn't necessarily use it too much uh in the notebooks other than introducing it. Um There are other approaches to building time series forecasts in Python. Um A nice list uh has been compiled by a github user that I've linked to here. Uh It has a lot of these different packages that you may be interested in checking out as well as explaining sort of what they do and what they might be used for.
So this might be a good place to start if you're looking to find more additional packages for Time Series in Python. OK. So that's gonna wrap it up for our focus on Time series um in this video as well as for all of the videos and lecture notebooks. If you're interested in learning more from our content, you can always check out the problem session notebook and the practice problems notebooks, there'll be a little bit
more there. Um As if you want to learn more, check out these links that I've provided. Ok. Have a great rest of your day. I hope you enjoyed this video. I enjoyed having you. Bye.