Ignacio Fuentes

Twitter @ignacioafuentes

Github: ignaciofuentes

Machine Learning is:

a way to give “computers the ability to learn without being explicitly programmed.”


Old concept

New implications

  • Product Personalization
  • Loyalty Programs
  • Next Best Offer
  • Customer Churn
  • Fraud Detection
  • Insurance Pricing
  • Stock Trading

Wield this power or it will wield you

install a ton of surveillance cameras

get really good at ml-powered facial recognition

match faces to IDs

monitor emotions...and manipulate them

invisibly track location

Scary uses of ML


Machine Learning

"A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.” (Tom Mitchell, 1997).

How to make a machine learn*

Gather a lot of data (text,images, sounds)

Divide that data into a training set and a test set

  • The training set is categorized (sorted by hand or by machine)
  • The test set is uncategorized

Use an algorithm to train a model with the training set by pairing input with expected output

Use the test set to test the accuracy of the training

rinse & repeat

Machine Learning is Easy!

DIY Machine Learning is hard

you need a lot of firepower & skillz

Let's leverage the cloud!

Let's build something!

NativeScript is…

an open source framework for building truly native mobile apps with JavaScript. Use web skills, like TypeScript, Angular, Vue, and CSS, and get native UI and performance on iOS and Android.


Rich, animated, “no compromise” native UI

(with shared UI code)

Search for

“Examples NativeScript”

in the iOS App Store or Google Play to try this app out for yourself.


Maximum code and skill reusability 

Architecture Choices


Thank you

ML for mobile apps

By Ignacio Fuentes

ML for mobile apps

Basic Deck

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