Artificial Intelligence and Machine Learning for the SWE

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Video and slides synchronized, mp3 and slide download available at URL https://bit.ly/2qEJFEZ. Rob Harrop describes both his own journey from traditional Software Engineer to AI/ML Engineer, and his experience building a development team with ML at the heart. Filmed at qconlondon.com. Rob Harrop is CEO at Skipjaq where he leads a team working on the cutting edge of machine-driven performance optimization. He is well known as a co-founder of SpringSource, the software company behind the wildly-successful Spring Framework. He was a core contributor to the Spring Framework and led the team that built dm Server (now Eclipse Virgo).

Technology

@robertharrop @skipjaqinc
AI/ML for Software
Engineers
Rob Harrop

InfoQ.com: News & Community Site
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ai-ml-swe
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@robertharrop @skipjaqinc
My Journey to Machine Learning
CEO @ SKIPJAQ
CTO and co-founder @ Bamboo Loans
Co-founder of SpringSource
Rob Harrop

@robertharrop @skipjaqinc
1: Machine Learning is
competitive advantage

@robertharrop @skipjaqinc
ML is rapidly becoming
competitive necessity

@robertharrop @skipjaqinc
2: ML is what’s next for
software engineers

@robertharrop @skipjaqinc
3: Good models don’t
happen by accident

@robertharrop @skipjaqinc
DevOps DevSecOps DevSecOps
ML

@robertharrop @skipjaqinc
“The way a team
plays as a whole
determines its
success.”
@robertharrop @skipjaqinc

@robertharrop @skipjaqinc
“The test of a first-rate intelligence is the ability to
hold two opposed ideas in mind at the same time and
still retain the ability to function”
F. Scott Fitzgerald

@robertharrop @skipjaqinc
Generalisation
vs.
Specialisation

@robertharrop @skipjaqinc
Individuals specialise
Teams generalise

@robertharrop @skipjaqinc
4: You Must Upskill

@robertharrop @skipjaqinc
Theory Practice Intuition
Statistics
Linear Algebra
Calculus
Optimisation
Regression
Classification
Deep Learning
Exploratory analysis
Data preparation
Iterative model development
Deploying and supporting models
Python/R
Numpy/Scikit/Pandas
Tensorflow/Keras/PyTorch
What type of learning problem do I
have?
What is
optimisation/regression/classification
really doing?
How can I think about forward and
backward propagation?
What types of things can I learn with a
neural network?

@robertharrop @skipjaqinc
Theory
Practice
Intuition

@robertharrop @skipjaqinc
“Intuition does not
come to an unprepared
mind.”
@robertharrop @skipjaqinc

@robertharrop @skipjaqinc
Learning Resources - Books

@robertharrop @skipjaqinc
Learning Resources - Online Courses
▸ Coursera Data Science Specialization - Brian Caffo and Roger Peng
▸ Coursera Deep Learning Specialization - Andrew Ng
▸ MIT OCW Linear Algebra - Gilbert Strang
▸ Coursera Calculus One & Two - Jim Fowler

@robertharrop @skipjaqinc
5: Bias is Everywhere

@robertharrop @skipjaqinc
“When a measure becomes a target, it
ceases to be a good measure.”
- Charles Goodhart

@robertharrop @skipjaqinc
Article 9, Section 1
Processing of personal data revealing racial or ethnic origin, political
opinions, religious or philosophical beliefs, or trade union membership, and
the processing of genetic data, biometric data for the purpose of uniquely
identifying a natural person, data concerning health or data concerning a
natural person's sex life or sexual orientation shall be prohibited.

@robertharrop @skipjaqinc
6: Transparency is Hard

@robertharrop @skipjaqinc
In Summary
▸ ML is competitive necessity. Don’t ignore it
▸ ML is software engineering
▸ Don’t make the mistakes of old; cross-functional teams win
▸ Now more than ever, ethics matter
▸ There’s a lot to learn, but it’s all valuable and it’s all fun

Watch the video with slide synchronization on
InfoQ.com!
https://www.infoq.com/presentations/ai-ml-
swe

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Artificial Intelligence and Machine Learning for the SWE

1. @robertharrop @skipjaqinc AI/ML for Software Engineers Rob Harrop

2. InfoQ.com: News & Community Site Watch the video with slide synchronization on InfoQ.com! https://www.infoq.com/presentations/ ai-ml-swe • Over 1,000,000 software developers, architects and CTOs read the site worldwide every month • 250,000 senior developers subscribe to our weekly newsletter • Published in 4 languages (English, Chinese, Japanese and Brazilian Portuguese) • Post content from our QCon conferences • 2 dedicated podcast channels: The InfoQ Podcast, with a focus on Architecture and The Engineering Culture Podcast, with a focus on building • 96 deep dives on innovative topics packed as downloadable emags and minibooks • Over 40 new content items per week

3. Purpose of QCon - to empower software development by facilitating the spread of knowledge and innovation Strategy - practitioner-driven conference designed for YOU: influencers of change and innovation in your teams - speakers and topics driving the evolution and innovation - connecting and catalyzing the influencers and innovators Highlights - attended by more than 12,000 delegates since 2007 - held in 9 cities worldwide Presented at QCon London www.qconlondon.com

4. @robertharrop @skipjaqinc My Journey to Machine Learning CEO @ SKIPJAQ CTO and co-founder @ Bamboo Loans Co-founder of SpringSource Rob Harrop

5. @robertharrop @skipjaqinc vs.

6. @robertharrop @skipjaqinc 1: Machine Learning is competitive advantage

7. @robertharrop @skipjaqinc ML is rapidly becoming competitive necessity

8. @robertharrop @skipjaqinc 2: ML is what’s next for software engineers

9. @robertharrop @skipjaqinc How -> How2

10. @robertharrop @skipjaqinc 3: Good models don’t happen by accident

11. @robertharrop @skipjaqinc DevOps DevSecOps DevSecOps ML

12. @robertharrop @skipjaqinc “The way a team plays as a whole determines its success.” @robertharrop @skipjaqinc

13. @robertharrop @skipjaqinc “The test of a first-rate intelligence is the ability to hold two opposed ideas in mind at the same time and still retain the ability to function” F. Scott Fitzgerald

14. @robertharrop @skipjaqinc Generalisation vs. Specialisation

15. @robertharrop @skipjaqinc Individuals specialise Teams generalise

16. @robertharrop @skipjaqinc 4: You Must Upskill

17. @robertharrop @skipjaqinc Theory Practice Intuition Statistics Linear Algebra Calculus Optimisation Regression Classification Deep Learning Exploratory analysis Data preparation Iterative model development Deploying and supporting models Python/R Numpy/Scikit/Pandas Tensorflow/Keras/PyTorch What type of learning problem do I have? What is optimisation/regression/classification really doing? How can I think about forward and backward propagation? What types of things can I learn with a neural network?

18. @robertharrop @skipjaqinc Theory Practice Intuition

19. @robertharrop @skipjaqinc “Intuition does not come to an unprepared mind.” @robertharrop @skipjaqinc

20. @robertharrop @skipjaqinc Practice

21. @robertharrop @skipjaqinc vs.

22. @robertharrop @skipjaqinc

23. @robertharrop @skipjaqinc Theory

24. @robertharrop @skipjaqinc

25. @robertharrop @skipjaqinc Learning Resources - Books

26. @robertharrop @skipjaqinc Learning Resources - Online Courses ▸ Coursera Data Science Specialization - Brian Caffo and Roger Peng ▸ Coursera Deep Learning Specialization - Andrew Ng ▸ MIT OCW Linear Algebra - Gilbert Strang ▸ Coursera Calculus One & Two - Jim Fowler

27. @robertharrop @skipjaqinc

28. @robertharrop @skipjaqinc 5: Bias is Everywhere

29. @robertharrop @skipjaqinc Human Bias

30. @robertharrop @skipjaqinc “When a measure becomes a target, it ceases to be a good measure.” - Charles Goodhart

31. @robertharrop @skipjaqinc Data Bias

32. @robertharrop @skipjaqinc Article 9, Section 1 Processing of personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership, and the processing of genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning health or data concerning a natural person's sex life or sexual orientation shall be prohibited.

33. @robertharrop @skipjaqinc Learned Bias

34. @robertharrop @skipjaqinc 6: Transparency is Hard

35. @robertharrop @skipjaqinc

36. @robertharrop @skipjaqinc In Summary ▸ ML is competitive necessity. Don’t ignore it ▸ ML is software engineering ▸ Don’t make the mistakes of old; cross-functional teams win ▸ Now more than ever, ethics matter ▸ There’s a lot to learn, but it’s all valuable and it’s all fun

37. Watch the video with slide synchronization on InfoQ.com! https://www.infoq.com/presentations/ai-ml- swe

Artificial Intelligence and Machine Learning for the SWE

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