Machine learning and time series data

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How do you apply machine learning to your time series? What can you accomplish by doing so? How do you do this? These questions and many more will get answered in this session led by our Machine Learning Developer Advocate, Anais Dotis-Georgiou.

Internet

Anais Dotis-Georgiou
Machine Learning and
Time Series Data

Agenda
● Intro to Machine Learning
● K-Means
○ What is K-Means Clustering?
○ How is it used for time series data?
○ Code showing how K-Means is used
● https://github.com/Anaisdg/K-Mean
s_Influx
● https://github.com/mrahtz/sanger-m
achine-learning-workshop/blob/mas
ter/Unsupervised%20Learning.ipyn
b

K-Means: How does it apply to time series data?
● Step back
● Why should we use machine learning for time series data at all?

K-Means: What is K-Means Clustering
● 4 major categories: unsupervised, semi-supervised, supervised, and
reinforcement learning
● K-Means is an unsupervised learning technique
● Supervised vs Unsupervised
● K-Nearest Neighbor

Some code showing how I used K-Means
● Time series data is clusterable?
● Steps anomaly detection:
○ Segmentation & Windowing
○ Clustering
○ Reconstruction
○ Alerting

Segmentation
Take your data that looks like this...

Clustering
● Segment size
determines
polynomial
shape
● Cluster number
can determine
how much
coefficients
matter

K-Means Links
● https://github.com/Anaisdg/K-Means_Influx
● https://www.influxdata.com/blog/why-use-k-means-for-time-series-data-part-o
ne/
● https://medium.com/@dganais/why-use-k-means-for-time-series-data-part-tw
o-690e771c0b36
● https://github.com/mrahtz/sanger-machine-learning-workshop

Holt-Winters Links
● https://grisha.org/blog/2016/01/29/triple-exponential-smoothing-forecasting/
● https://docs.influxdata.com/influxdb/v1.6/query_language/functions/#holt-wint
ers
●

LoudML Links
● https://www.influxdata.com/blog/applying-machine-learning-models-to-influxd
b-with-loud-ml-docker-for-time-series-predictions/
● https://loudml.io/

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Machine learning and time series data

1. Anais Dotis-Georgiou Machine Learning and Time Series Data

2. Welcome

3. Agenda ● Intro to Machine Learning ● K-Means ○ What is K-Means Clustering? ○ How is it used for time series data? ○ Code showing how K-Means is used ● https://github.com/Anaisdg/K-Mean s_Influx ● https://github.com/mrahtz/sanger-m achine-learning-workshop/blob/mas ter/Unsupervised%20Learning.ipyn b

4. K-Means: How does it apply to time series data? ● Step back ● Why should we use machine learning for time series data at all?

5. Moving Average

6. Stdev

7. Quartile Range

10. K-Means: What is K-Means Clustering ● 4 major categories: unsupervised, semi-supervised, supervised, and reinforcement learning ● K-Means is an unsupervised learning technique ● Supervised vs Unsupervised ● K-Nearest Neighbor

11.

12.

13.

14.

15. ● Euclidean: ● Centroid’s position: ●

16. Some code showing how I used K-Means ● Time series data is clusterable? ● Steps anomaly detection: ○ Segmentation & Windowing ○ Clustering ○ Reconstruction ○ Alerting

17. Segmentation Take your data that looks like this...

18. Turn it into this...

19. Clustering ● Segment size determines polynomial shape ● Cluster number can determine how much coefficients matter

20. Resources

21. K-Means Links ● https://github.com/Anaisdg/K-Means_Influx ● https://www.influxdata.com/blog/why-use-k-means-for-time-series-data-part-o ne/ ● https://medium.com/@dganais/why-use-k-means-for-time-series-data-part-tw o-690e771c0b36 ● https://github.com/mrahtz/sanger-machine-learning-workshop

22. Holt-Winters Links ● https://grisha.org/blog/2016/01/29/triple-exponential-smoothing-forecasting/ ● https://docs.influxdata.com/influxdb/v1.6/query_language/functions/#holt-wint ers ●

23. LoudML Links ● https://www.influxdata.com/blog/applying-machine-learning-models-to-influxd b-with-loud-ml-docker-for-time-series-predictions/ ● https://loudml.io/

24. Thank You

Machine learning and time series data

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