Machine Learning for Non-Technical People - Turing Fest 2019

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Machine Learning/AI is becoming more and more accessible and will free you up to work on higher level thinking. ANYONE can come up with the next big ML/AI application. What will you solve?

Technology

Machine Learning for Marketers
@BritneyMuller
Senior SEO Scientist

Machine Learning is becoming more accessible &
will free you up to work on higher level strategy

Machine Learning will free us up to work on higher
level strategy.

#1 Machine Learning Examples
#2 What ML Can/Can’t Solve
#3 Tools & Resources
Machine Learning for Marketers

What is Machine Learning?
Machine Learning is a subset of AI that
combines statistics & programming
to give computers the ability to “learn”
without explicitly being programmed.

If Machine Learning was a car
data would be the fuel.

ML doesn’t solve well for soft/people skills.

Driving
Surgery
Construction
Teachers
Nurses
Childcare
ML ✅ ML ❌

You don’t have to be a Data Scientist to think of
the next brilliant ML application!

Machine Learning is becoming more accessible & will
free you up to do more strategic work.

Automate Meta Descriptions
@BritneyMuller

Use Google's own NLP to know how G is understanding your
content (vs your competitors)!!!

Our Data Science Team at Moz is innovating in
this space & creating ground-breaking solutions
coming soon!

Getting Started
• Search ‘Harvard CS109’ in GitHub
• Google CodeLabs – Break things!!!
• MNist --The “Hello World!” of Machine Learning
• Colab Notebooks OR Jupyter Notebooks
• Learn With Google AI
• Image-net.org
• Kaggle
• MonkeyLearn

• Yearning Learning (free book preview by Andre Ng)
• Neural Networks & Deep Learning
• Correlation vs Causation (by Dr. Pete!)
• Exploring Word2Vec
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• The Shallowness of Google Translate
• TF-IDF
• LSI
• LDA
• Learn Python
• Massive Open Online Courses
• Coursera Machine Learning
• RAY by Professors at UC Berkeley
Advanced Resources

ML Takeaways:
➢ 1. Machine Learning is statistics + programming
➢ 2. ML models are only as good as their training data
➢ 3. YOU can create a ML model today!!!
➢ “You aren’t trying hard enough unless you’re breaking stuff!” – B.Muller
➢ 4. ML will help Marketers/Everyone level up
➢ 5. Diversity is paramount in ML

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Machine Learning for Non-Technical People - Turing Fest 2019

1. Machine Learning for Marketers @BritneyMuller Senior SEO Scientist

3. @BritneyMuller

4. @BritneyMuller

5. Machine Learning is becoming more accessible & will free you up to work on higher level strategy

10.

11. @BritneyMuller

12. @BritneyMuller

13.

14.

15.

16. @BritneyMuller

17. bit.ly/rand-b @BritneyMuller

18. #TTTLIVE19 bit.ly/tf-for-poets

19. #TTTLIVE19

20. #TTTLIVE19

21. Machine Learning will free us up to work on higher level strategy.

22. #1 Machine Learning Examples #2 What ML Can/Can’t Solve #3 Tools & Resources Machine Learning for Marketers

23. What is Machine Learning? Machine Learning is a subset of AI that combines statistics & programming to give computers the ability to “learn” without explicitly being programmed.

24.

25. But, how does it ‘learn’!?

26.

27.

28. If Machine Learning was a car data would be the fuel.

29.

30. 10 Year Challenge?

31. ML doesn’t solve well for soft/people skills.

32. Driving Surgery Construction Teachers Nurses Childcare ML ✅ ML ❌

33.

34.

35. You don’t have to be a Data Scientist to think of the next brilliant ML application!

36. Machine Learning is becoming more accessible & will free you up to do more strategic work.

37. #1 Machine Learning Examples #2 What ML Can/Can’t Solve #3 Tools & Resources Machine Learning for Marketers

38.

39.

40.

41. Automate Videos

42.

43. Automate Transcriptions

44.

45. Automate Meta Descriptions @BritneyMuller

46. @BritneyMuller

47. @BritneyMuller

48.

49. #TTTLIVE19

50.

51.

52.

53.

54.

55. @BritneyMuller

56. Use Google's own NLP to know how G is understanding your content (vs your competitors)!!!

57.

58. #TTTLIVE19

59. CPU > GPU > TPU

60. Our Data Science Team at Moz is innovating in this space & creating ground-breaking solutions coming soon!

61. Getting Started • Search ‘Harvard CS109’ in GitHub • Google CodeLabs – Break things!!! • MNist --The “Hello World!” of Machine Learning • Colab Notebooks OR Jupyter Notebooks • Learn With Google AI • Image-net.org • Kaggle • MonkeyLearn

62. • Yearning Learning (free book preview by Andre Ng) • Neural Networks & Deep Learning • Correlation vs Causation (by Dr. Pete!) • Exploring Word2Vec • The Zipf Mystery • BigML • Targeting Broad Queries in Search • Project Mosaic Books • Algorithmia • How to eliminate bias in data driven marketing • TensorFlow Dev Summit 2018 [videos] • NLP Sentiment Analysis • Talk 2 Books • The Shallowness of Google Translate • TF-IDF • LSI • LDA • Learn Python • Massive Open Online Courses • Coursera Machine Learning • RAY by Professors at UC Berkeley Advanced Resources

63. ML Takeaways: ➢ 1. Machine Learning is statistics + programming ➢ 2. ML models are only as good as their training data ➢ 3. YOU can create a ML model today!!! ➢ “You aren’t trying hard enough unless you’re breaking stuff!” – B.Muller ➢ 4. ML will help Marketers/Everyone level up ➢ 5. Diversity is paramount in ML

64. What Will You Solve For?

65. Thank You!

Machine Learning for Non-Technical People - Turing Fest 2019

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