courses:psaw:lab_timeseries

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Next revision		 Previous revision
courses:psaw:lab_timeseries [2022/05/11 14:00] – created - external edit 127.0.0.1courses:psaw:lab_timeseries [2025/04/08 08:18] (current) – [Learn more!] jeremi
Line 10: Line 10:
 ==== Materials ==== ==== Materials ====
  
-  - Instead of a lecture, we go straight to the Q&A session with a short series of questions to "warm up" (based on the textbook). Also,  in the hands-on session, the most important content is summarized alongside the practical activities. 
   - Q&A Session:   - Q&A Session:
     - How time series data differ from other data?     - How time series data differ from other data?
Line 21: Line 20:
   - Advanced practice session:   - Advanced practice session:
     - If you want to evaluate more advanced models, go to the optional Advanced section in the notebook.     - If you want to evaluate more advanced models, go to the optional Advanced section in the notebook.
-  - Report: +
-    - Send the final version of the notebook (to download it, click in Google Colab: ''File > Download > Download .ipynb''). Make sure you have done all required **6 tasks**.+
  
 ==== Learn more! ==== ==== Learn more! ====
  
   * R.J. Hyndman & G. Athanasopoulos, G. -- [[https://otexts.com/fpp3/|Forecasting: principles and practice]] (OTexts, 2021) -- interesting book, full text online, code in R   * R.J. Hyndman & G. Athanasopoulos, G. -- [[https://otexts.com/fpp3/|Forecasting: principles and practice]] (OTexts, 2021) -- interesting book, full text online, code in R
 +  * Brockwell, P.J., Davis, R.A. (Eds.), 2002. Introduction to Time Series and Forecasting, Springer Texts in Statistics. Springer New York, New York, NY. [[https://doi.org/10.1007/b97391|DOI:10.1007/b97391]], [[http://home.iitj.ac.in/~parmod/document/introduction%20time%20series.pdf| full text pdf]] -- a standard reference textbook; old but gold
 +  * Aileen Nielsen, tutoriale video: [[https://youtu.be/zmfe2RaX-14|Time Series Analysis – PyCon 2017]], [[https://youtu.be/v5ijNXvlC5A|Modern Time Series Analysis – SciPy 2019]]
 +  * [[https://cran.r-project.org/web/views/TimeSeries.html| CRAN Task View: Time Series Analysis]] -- description of almost all R packages for time series analysis
 +  * [[https://github.com/timeseriesAI/tsai|State-of-the-art Deep Learning library for Time Series and Sequences]] -- one of Python libraries collecting neural network models for time series classification 
  • courses/psaw/lab_timeseries.1652277640.txt.gz
  • Last modified: 4 years ago
  • by 127.0.0.1