Brief introduction to machine learning in the context of a tool for business -- specifically tech startups.

1. Building expertise on demand.
HOW MACHINE LEARNING
WORKS FOR BUSINESS

2. TODAY’S GOAL
Leave with a firm grasp on how machine learning
can be a tool and an opportunity for your business.

3. OUR JOURNEY
● Context
● Choosing the right tool
● Putting it to work
● The hurdles

4. WHAT IS MACHINE
LEARNING?
A brief introduction.

5. SOFTWARE IS EATING THE WORLD
Everything is becoming code.
Software automates, simplifies, and
accelerates business.

6. BUT...
Someone needs to write the code/logic.

7. THE TRADITIONAL WAY
Handwritten logic.
If / Then / Else

8. THE PROBLEM
Complex situations require
complex2
software logic.

9. THE SOLUTION
Trained logic using historical data.
Model
tripID hasEggs eggsBought milkBought
1 1 6 1
2 0 0 2
3 1 6 1
4 1 8 1
5 0 0 1
6 1 6 1
7 0 0 3
0011001101011101
0101100111010
11001001101
Stored as a
mathematical
model.
Finds patterns in
the data.

10. WHAT IT LOOKS LIKE
console.aws.amazon.com/machinelearning/home?region=us-east-1#/datasources

11. ML IS EATING THE SOFTWARE
All applications are becoming “smart” — with
unprecedented complexity in logic.
Machine learning automates, simplifies, and
accelerates software.

12. MURKY LANDSCAPE
Artificial Intelligence
Machine Understanding (?)
Pattern recognition
Classification
Prediction
Can only do one thing
Brute-force approach
Autonomous decisions
Universally applicable
Intuition approach
Google DeepMind
Amazon Machine Learning
Natural language processing
Computer vision
Optimization
IBM Watson
Classic learning
Multi-tiered
deep learning
neural networks
Deep learning
neural network
Explicit ProgrammingHandwritten
Machine Learning
logiccomplexity

13. CHOOSING
THE RIGHT TOOL
Exploring the major machine learning
architectures.

14. No “hidden”
layers
“CLASSIC” LEARNING
playground.tensorflow.org

15. Fast, simple predictions.
Product recommender
Price prediction
Behavior prediction
Typically, features are predefined.
“CLASSIC” LEARNING

16. 1-2 “hidden”
layers
“SHALLOW” LEARNING

17. Deep learning has eclipsed.
“SHALLOW” LEARNING

18. >2 “hidden”
layers
“DEEP” LEARNING

19. Complex, contextual
understanding.
Computer vision
Natural language processing
Uncovering hidden insights
Often, features are learned
directly from the data.
“DEEP” LEARNING
Many Different Types
● Deep Belief (DBN)
● Convolutional (CNN)
● Recurrent (RNN)

20. CLASSIFICATION
via: wjscheirer.com

21. Structured
Unstructured
Reinforcement
TRAINING

22. FINDING A CONTEXT FOR
MACHINE LEARNING
How to wrap your head around this
massive subject.

23. Expertise on demand.
Train your ideal decision-making processes and tasks,
then execute them anytime, anywhere, at any scale.
PUT IT TO WORK

24. TOOL OR OPPORTUNITY?
How can you create expertise on demand
for you or your customers?

25. Expertise on demand.

26. UNIVERSAL EXCELLENCE
A proven path to
business success is
staffing “the best.”
And, imagine your “best”
continually getting
better every day.
● Hiring expert
● SEO expert
● PR expert
● Social media expert
● Researching expert
And more...

27. EXPERT MARKETER
Consistently presents the right message, to the right
person, at the right time
● Understands your customers better than any high-
priced agency ever could
● Dynamically personalizes each individual
experience
● Accurately predicts audience behavior

28. EXPERT FORECASTER
● Revenue
● Inventory
● Taxes
● Expenses
● Staffing

29. EXPERT WRITER
From SEO meta tags to novels.
● Can be trained to any “voice”
● Deep topic research and digestion
● Instantly learn from world experts
● Accurate fact checks
● No more hiring writers
● No more typos

30. EXPERT ADVISOR
Imagine what you could
accomplish with your
own personal JARVIS.
He’s closer than you think.

31. Expertise on demand.

32. WHY WE LOVE COMPUTERS
Any time, any where, any scale.
No vacations, no sleep, no sick days.

33. THE HURDLES
Exploring the common sticking points.

34. IT’S GETTING EASIER EVERY DAY
● Purpose-built APIs
● Pre-trained models
● Open source projects
But...

35. We’re headed into a world, where
we can know anything, anytime.
So the quality of the questions you
ask determines your success.
“Wrong questions get wrong answers.”
~Gregory
The Seventh Son (2014)
QUESTIONS MATTER

36. FEED THE BEAST
Build your data stockpile.
Historically we don’t save data,
because we didn’t look at it.
Now we can learn even more from it
— without looking at it.
So hoard as much as you can.

37. RECAP
● Train complex software logic
● Deploy expertise on-demand
● Ask empowering questions
● Hoard your data

38. GOAL CHECK
Feel like you have a firm grasp on how machine
learning can be a tool and an opportunity for your
business?

39. THOUGHTS?
Upsides & downsides
to “expertise on demand?”

40. UNLEASH YOUR BUSINESS
EMBRACE EXPONENTIAL
10xnation.com