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Introduction to Deep Learning

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Video duration
00:41:06
Language
English
Abstract
This talk will teach you the fundamentals of machine learning and give you a sneak peek into the internals of the mystical black box. You'll see how crazy powerful neural networks can be and understand why they sometimes fail horribly.

Computers that are able to learn on their own. It might have sounded like science-fiction just a decade ago, but we're getting closer and closer with recent advancements in Deep Learning. Or are we?

In this talk, I'll explain the fundamentals of machine-learning in an understandable and entertaining way. I'll also introduce the basic concepts of deep learning. With the current hype of deep learning and giant tech companies spending billions on research, understanding how those methods works, knowing the challenges and limitations is key to seeing the facts behind the often exaggerated headlines.

One of the most common applications of deep learning is the interpretation of images, a field that has been transformed significantly in recent years. Applying neural networks to image data helps visualising and understanding many of the faults as well as advantages of machine learning in general. As a research scientist in the field of automated analysis of bio-medical image data, I can give you some insights into these as well as some real-world applications.

Talk ID
9386
Event:
35c3
Day
1
Room
Adams
Start
5:10 p.m.
Duration
00:40:00
Track
Science
Type of
lecture
Speaker
teubi
Talk Slug & media link
35c3-9386-introduction_to_deep_learning

Talk & Speaker speed statistics

Very rough underestimation:
151.5 wpm
829.8 spm
158.8 wpm
866.7 spm
100.0% Checking done100.0%
0.0% Syncing done0.0%
0.0% Transcribing done0.0%
0.0% Nothing done yet0.0%
  

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Talk & Speaker speed statistics with word clouds

Whole talk:
151.5 wpm
829.8 spm
networkpicturelearningtrainingmodelinputdataoutputexamplepicturesimagedeephorsenumberlearncasevaluesnumbersweightsencodeneuroncalledneuralprocesssimpleteubicallangelcomplexreallayersgeneratorimagesparametersgeneratelayerworkhorsesquestiontraincourseworksfindstartgreatunicornsfullysizecomputermachine
teubi:
158.8 wpm
866.7 spm
networkpicturemodellearningtraininginputoutputdataexampleimagedeeplearnhorsecasepicturesweightsencodeneuronnumbersnumbercallcomplexsimpleprocesscalledvaluesparametersrealneurallayerlayersgeneratorgenerateworktrainhorsesfindworksimagesunicornscoursefullycomputerstatisticalrabbitsanimalsizemappingtruthpixels