> For the complete documentation index, see [llms.txt](https://opencampus.gitbook.io/opencampus-machine-learning-program/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/time-series-prediction/references-books.md).

# References / Books

YES.....books.....you may heard about it....these things were used in former times   ;-)

Last but not least - here are some very good book references. It is not required or requested to buy any of these books. If you are enrolled as a student at CAU, FH Kiel or another university you might have access to these books via the SpringerLink of your home institution. They cover the course material quite well and provide GitHub-Repositories for the codes which where used throughout the book. Unfortunately there is no 1:1-Coursera course matching these books perfectly - but we will do our best ;-)

{% embed url="<https://link.springer.com/book/10.1007/978-1-4842-7150-6>" %}
<https://github.com/Apress/advanced-forecasting-python>
{% endembed %}

{% embed url="<https://link.springer.com/book/10.1007/978-1-4842-8978-5>" %}
<https://github.com/Apress/time-series-algorithm-recipes>
{% endembed %}

{% embed url="<https://link.springer.com/book/10.1007/978-1-4842-5992-4>" %}
<https://github.com/Apress/hands-on-time-series-analylsis-python>
{% endembed %}

{% embed url="<https://www.packtpub.com/product/machine-learning-for-time-series-with-python/9781801819626>" %}
<https://github.com/PacktPublishing/Machine-Learning-for-Time-Series-with-Python>
{% endembed %}

{% embed url="<https://www.packtpub.com/product/modern-time-series-forecasting-with-python/9781803246802?utm_source=github&utm_medium=repository&utm_campaign=9781803246802>" %}
<https://github.com/PacktPublishing/Modern-Time-Series-Forecasting-with-Python>
{% endembed %}

{% embed url="<https://www.packtpub.com/product/time-series-analysis-with-python-cookbook/9781801075541>" %}
<https://github.com/PacktPublishing/Time-Series-Analysis-with-Python-Cookbook>
{% endembed %}

{% embed url="<https://in.bpbonline.com/products/time-series-forecasting-using-deep-learning?_pos=1&_sid=670c171d5&_ss=r>" %}
<https://github.com/bpbpublications/Time-Series-Forecasting-using-Deep-Learning>
{% endembed %}

{% embed url="<https://link.springer.com/book/10.1007/978-3-031-13584-2>" %}
<https://github.com/QuantLet/pyTSA/>
{% endembed %}

{% embed url="<https://www.manning.com/books/time-series-forecasting-in-python-book?utm_source=marcopeix&utm_medium=affiliate&utm_campaign=book_peixeiro_time_10_21_21&a_aid=marcopeix&a_bid=8db7704f>" %}
<https://github.com/marcopeix/TimeSeriesForecastingInPython/tree/master>
{% endembed %}

Some additional course material and MOOCs if you want you expand your knowledge at your own pace:

{% embed url="<https://www.coursera.org/learn/practical-time-series-analysis>" %}
This is a nice time series course with a focus on R/RStudio. It goes slightly deeper then our first course but lacks machine learning techniques. Nevertheless a very good ranked course and worth doing it - if you like to deepen your knowledge.
{% endembed %}

{% embed url="<https://otexts.com/fpp2/>" %}
This book is freely available and provides additional information. Focus on R/RStudio.
{% endembed %}


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