Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Machine Learning for Non-Technical People - Turing Fest 2019

150 views

Published on

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?

Published in: Technology
  • Be the first to comment

  • Be the first to like this

Machine Learning for Non-Technical People - Turing Fest 2019

  1. 1. Machine Learning for Marketers @BritneyMuller Senior SEO Scientist
  2. 2. @BritneyMuller
  3. 3. @BritneyMuller
  4. 4. Machine Learning is becoming more accessible & will free you up to work on higher level strategy
  5. 5. @BritneyMuller
  6. 6. @BritneyMuller
  7. 7. @BritneyMuller
  8. 8. bit.ly/rand-b @BritneyMuller
  9. 9. #TTTLIVE19 bit.ly/tf-for-poets
  10. 10. #TTTLIVE19
  11. 11. #TTTLIVE19
  12. 12. Machine Learning will free us up to work on higher level strategy.
  13. 13. #1 Machine Learning Examples #2 What ML Can/Can’t Solve #3 Tools & Resources Machine Learning for Marketers
  14. 14. 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.
  15. 15. But, how does it ‘learn’!?
  16. 16. If Machine Learning was a car data would be the fuel.
  17. 17. 10 Year Challenge?
  18. 18. ML doesn’t solve well for soft/people skills.
  19. 19. Driving Surgery Construction Teachers Nurses Childcare ML ✅ ML ❌
  20. 20. You don’t have to be a Data Scientist to think of the next brilliant ML application!
  21. 21. Machine Learning is becoming more accessible & will free you up to do more strategic work.
  22. 22. #1 Machine Learning Examples #2 What ML Can/Can’t Solve #3 Tools & Resources Machine Learning for Marketers
  23. 23. Automate Videos
  24. 24. Automate Transcriptions
  25. 25. Automate Meta Descriptions @BritneyMuller
  26. 26. @BritneyMuller
  27. 27. @BritneyMuller
  28. 28. #TTTLIVE19
  29. 29. @BritneyMuller
  30. 30. Use Google's own NLP to know how G is understanding your content (vs your competitors)!!!
  31. 31. #TTTLIVE19
  32. 32. CPU > GPU > TPU
  33. 33. Our Data Science Team at Moz is innovating in this space & creating ground-breaking solutions coming soon!
  34. 34. 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
  35. 35. • 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
  36. 36. 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
  37. 37. What Will You Solve For?
  38. 38. Thank You!

×