Britney Muller - Machine learning for marketers (Turing Fest 2019)

Machine Learning is becoming more and more accessible to non-technical individuals & will free you up to work on more strategic efforts.

The biggest bottleneck in Machine Learning/AI is people like YOU with domain expertise and great ideas! Help your industry innovate by attending this Machine Learning crash course. You'll walk away with a foundational understanding of ML, the tools necessary to implement ML models and the confidence to consider ways in which it can be applied to help you with everyday work.

Transcript

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
11. @BritneyMuller
12. @BritneyMuller
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.
25. But, how does it ‘learn’!?
28. If Machine Learning was a car data would be the fuel.
30. 10 Year Challenge?
31. ML doesn’t solve well for soft/people skills.
32. Driving Surgery Construction Teachers Nurses Childcare ML ✅ ML ❌
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
41. Automate Videos
43. Automate Transcriptions
45. Automate Meta Descriptions @BritneyMuller
46. @BritneyMuller
47. @BritneyMuller
49. #TTTLIVE19
55. @BritneyMuller
56. Use Google's own NLP to know how G is understanding your content (vs your competitors)!!!
58. #TTTLIVE19
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!