Machine learning sounds like something out of reach of the average marketer. Last year IBM opened up their super computer Watson, Microsoft launced Azure and also Amazon opened up their Machine Learning models to be commercially used. During this session I’ll introduce the concept of machine learning and share a few practical examples on how you can use it to optimize your SEO processes.

1. International Freelance SEO

10. 

13. International Freelance
SEO
Brand Ambassador
Majestic
Cycling & Skating
Science: Physics in
particular
http://www.cyclingacrosstheworld.com

14. “A computer program is said to learn from
experience E with respect to some task T
and some performance measure P, if its
performance on T, as measured by P,
improves with experience E.” -Tom Mitchell,
Carnegie Mellon University

15. E: 50 years of data about housing prices in
Brighton
T: Pricing prediction to sell at right price
P: the better price predictions it gives, the
better future predictions will be

16. The goal of ML is never to make “perfect”
guesses, because ML deals in domains where
there is no such thing. The goal is to make
guesses that are good enough to be useful.
British mathematician and professor of statistics
George E. P. Box that “all models are wrong, but
some are useful”

17. Document Sentiment analysis of a specific URL:
{
"status": "OK",
"url": " https://www.notprovided.eu/why-not-use-googles-wmt-data/ ",
"totalTransactions": "1",
"language": "english",
"docSentiment": [
{
"mixed": "1",
"score": "0.412838",
"type": "positive"
}
]
}

19. You know
what you are
looking for
What do these
datapoints have
in common?

20. E: 50 years of data about housing prices
in Brighton
T: Pricing prediction to sell at right price
P: the better price predictions it gives, the
better future predictions will be

21. No rules teached. It took Google’s AI thousands of games to detect losing was probably bad

23. https://www.udacity.com/course/viewer#!/c-ud120/l-2254358555/m-2374468553

24. Best to start with:
• https://www.coursera.org/learn/machine-learning
by Andrew Ng (Baidu, former Google Brain)
• Tom Mitchell lectures:
http://www.cs.cmu.edu/~tom/10601_fall2012/lect
ures.shtml
• https://work.caltech.edu/telecourse.html Caltech
ML course

25. http://pdf.th7.cn/down/files/1312/machine_learning_for_hackers.pdf

27. Mainly use pre trained models:
– Spam classification of user generated content
(comments & reviews)
– Content classification
– Text extraction from pages
– Data gathering

28. • Query classification
• Recommendation engines: internal linking
based on both e-commerce, user
behaviour and SEO metrics.

29. http://blog.mashape.com/list-of-50-
machine-learning-apis/

32. • No NLP or Machine Learning knowledge is
required.
• Lot’s of pre trained models & you can train
your own models

39. Machine Learning based scraping,Yeah!

41. https://www.notprovided.eu/7-tools-web-scraping-use-
data-journalism-creating-insightful-content/

43. 1. Collected all hotel reviews
2. Check sentiment and main entities
3. Upload search volume and e-commerce
data per hotel
4. Update UX & internal linking accordingly

44. ?

45. 1. Collected all hotel reviews
2. Plotted against time
3. Extract upcoming entities and sentiments
4. Predict future search behaviour
5. Create landingpages for future targeting

47. How about using Machine Learning

49. Tip: Check both the homepage and the specific link page!

53. Input: a URL -> output: plain text

55. Input text without
HTML!

59. • A list of links containing
– Content language
– Content topic
– Spam probability
– Content sentiment (if wanted)
– Prioritized on language relevancy

60. • 10.000+ keywords? Use a ML classifier
• Check for entities like places for local
• Buying intent vs informational

61. Persona
Customer
journey stage
Page Type
Local
identifier
Tag Keyword
Leisure NL Awareness Product Yes Campingaz Campingaz Munich
Leisure NL Awareness Informational No terrasverwarmer
Leisure NL Awareness Informational No terrasverwarming
Leisure NL Awareness Informational No BBQ gasbarbecue
Leisure NL Awareness Informational No BBQ gas bbq
Leisure NL Consideration Informational No Generic gasfles
Leisure NL Retention Informational No Generic gasfles vullen
Leisure NL Retention Informational No Branded primagaz
Leisure NL Consideration Informational No Generic gasfles kopen
B2B-industrie Awareness Informational No LNG lng
Leisure NL Consideration Product No Generic gasflessen
Leisure NL Awareness Informational No Generic kookplaat gas
Energie Awareness Informational No Propaan propaan
Leisure NL Awareness Informational No Butaan butaan

64. "I liked the book you gave me yesterday, but
the rest of my day was terrible."

70. • Restructure website content based on a
set taxonomy of topics
• Extract texts from top 30 and define text
requirements (eg. Searchmetrics module)
• Purchase prediction for new queries

74. • Use Google Tensorflow to identify image
contents
• Crawl topic related content
• Generate automatic descriptions and paragraph
text
• Build a image library site including text, good for
SEO 
https://databricks.com/blog/2016/01/25/deep-learning-with-spark-and-tensorflow.html

75. https://www.quora.com/Machine-Learning/How-
do-I-learn-machine-learning-1

76. 