dlighted datafit podcast

#4 DETECTING MALARIA THROUGH MACHINE LEARNING ON A BUDGET WITH EDUARDO PEIRE

November 25, 2018
dlighted datafit podcast
#4 DETECTING MALARIA THROUGH MACHINE LEARNING ON A BUDGET WITH EDUARDO PEIRE
Chapters
00:00:00
Intro
00:06:00
What is Deep Learning and predictive models like decision trees.
00:11:30
Building the first prototype of the microscope
00:18:31
How does it work?
00:23:00
What is the vision behind AIScope?
00:25:00
Is it possible that AI becomes better as doctors?
00:28:00
What happens if AI makes a mistake?
00:31:00
How can you support AIScope?
00:36:00
How you can become a Data Scientist?
00:41:00
What does data literacy means for Eduardo?
dlighted datafit podcast
#4 DETECTING MALARIA THROUGH MACHINE LEARNING ON A BUDGET WITH EDUARDO PEIRE
Nov 25, 2018
Tizian Kronsbein & Simon Frey
Ai Scope dedicated its focus to diagnose global diseases such as malaria, tuberculosis and intestinal parasites in every isolated village with the help of artificial intelligence. Using Machine Learning, they developed a portable and ultra cheap solution, and open-sourced it!
Show Notes Chapter Markers

Eduardo is an AI and ML Consultant and the Founder AiScope.
With AI Scope he is absolutely doing something great and good for the world.

Ai Scope dedicated its focus to diagnose global diseases such as malaria, tuberculosis and intestinal parasites in every isolated village with the help of artificial intelligence. Using Machine Learning, they developed a portable and ultra cheap solution, and open-sourced it!

We talked about their development process and their vision. We also discussed whether or not Artificial Intelligence can make doctors obsolete in the future, how you become a data scientist but also if it is necessary to be data literate at all.

You can find more information on AI Scope here: http://aiscope.net
You can find Eduardo here: https://www.linkedin.com/in/eduardopeire/
Data Science Sleepover: http://aiscope.net/data-science-sleep-over/

Good explanation of Deep Learning: https://medium.com/@RosieCampbell/demystifying-deep-neural-nets-efb726eae941
The difference between false positives and false negatives: https://developers.google.com/machine-learning/crash-course/classification/true-false-positive-negative

John Hopkins University’s Online Course on Data Science: https://ep.jhu.edu/programs-and-courses/programs/data-science

The kit with the books from all of our guests: https://kit.com/dlighted/guest-book-recommendations.

What is Deep Learning and predictive models like decision trees.
Building the first prototype of the microscope
How does it work?
What is the vision behind AIScope?
Is it possible that AI becomes better as doctors?
What happens if AI makes a mistake?
How can you support AIScope?
How you can become a Data Scientist?
What does data literacy means for Eduardo?
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