This deck was presented as part of a company initiative, #TechTalks, aimed to provide a space for the sharing and exploration of topics of interest in the industry.
Presented by: Javier Fonseca, Back-end developer
How to Troubleshoot Apps for the Modern Connected Worker
Machine learning: Koombea TechTalks
1. Machine Learning
... or how Google predicts
everything about you
By: Javier Fonseca
Back-end developer
2. What is Google?
Is it an Internet search company?
Is it an online
advertising service
company?
As per the Wikipedia definition, it is an Internet-related services company.
... a pretty broad definition, isn't it?
3. But what about their mission?
“Organize the world’s information and make it universally
accessible and useful.”
Source: https://www.google.com/intl/en/about/our-company/
4. How is Google able to achieve such a noble
goal?
● They store tons of information.
● They apply Machine Learning to it.
5. Some information Google tracks about users
● Searches
● "Ok Google" activity
● Web browsing activity
● Location history
● YouTube searches
● YouTube "Not Interested" feedback
● YouTube watches
● Mobile apps you used
● Google Ads settings
Source: https://myactivity.google.com/
6. How does Google use that information?
● To improve their services.
● And... to sell your personal data? NO!
● But... to make ads relevant.
Source: https://privacy.google.com/how-ads-work.html
Source: https://privacy.google.com/your-data.html
19. Further Information
Software resources
● scikit-learn: machine learning in Python
● Anaconda: distribution of Python and R for large scale data
processing
● TensorFlow: An open-source software library for Machine
Intelligence
● Andrei Beliankou: Machine Learning with Ruby (curated list of links)
21. Further Information
Basic courses
● Adam Geitgey: Machine Learning is Fun! (8-part blog)
● Udacity Picodegree: a friendly introduction to Machine Learning
● Udacity: Intro to Machine Learning
● Google: Machine Learning recipes with Josh Gordon
● Coursera: Machine Learning
22. Further Information
Advanced Courses
● University of Stanford: CS231n Convolutional Neural Networks for
Visual Recognition
● fast.ai: Practical Deep Learning for Coders
● MIT Press: Deep Learning Book
● Udacity: Deep Learning by Google
● Coursera: Deep Learning specialization