fundamentals of deep learningnvidia, deep learning institute fundamentals of deep learning...

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Raymond Ptucha, Rochester Institute of TechnologyNVIDIA, Deep Learning Institute

Fundamentals of Deep Learning

Electronic Imaging 2019: SC20January 15, 2019, 8:30am-12:45pm

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Fair Use AgreementThis agreement covers the use of all slides in this document, please read carefully.

• You may freely use these slides, if:– You send me an email telling me the conference/venue/company name

in advance, and which slides you wish to use.– You receive a positive confirmation email back from me.– My name (R. Ptucha) appears on each slide you use.

(c) Raymond Ptucha, rwpeec@rit.edu

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Agenda

• Part I- Intuition and Theory– 8:35-9:15pm: Introduction– 9:15-10:00pm: Convolutional Neural Networks– 10:00-10:40pm: Recurrent Neural Networks

• 10:40-11:00pm: Break

• Part II- Hands on– 11:00am-12:45pm: Hands-on exercises

DEEP LEARNING FUNDAMENTALS FOR COMPUTER VISION

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• Train first network• Introduce Image

Classification• Necessary ingredients for

successful training

Training

• Role of Neural Networks in Applications

• Building around networks

Deployment• Improving accuracy• Improving capability• Solving novel problems

• Changing layers of network• Beyond Image

Classification

Performance

This Course: Deep Learning Fundamentals

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Work through Introduction Section

• Navigate to:• courses.nvidia.com/dli-event• Browser Recommendation: Chrome

• Event code: EIC_CV2.0_ AMBASSADOR_JA19• Create an Account• Work through the Introduction Section and

‘Start’ launching your first GPU task

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When done viewing slides, scroll down

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Answer question, then choose next

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When done viewing slides, scroll down

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Click Start

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It will take a few minutesWhile it is loading, read intro material…

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Click Launch Task when ready

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This will open up a new tab.You can go back and forth between original and this new tab

new taboriginal tab

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When you click Open digits, a third tab will open, now you can navigate between all three tabs

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After the digits window opens, follow directions from this window and perform tasks in digits window.

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If you get “lost” in DIGITS, click this to return to this page

Use this to create or work on datasets

Use this to create or work on neural network models

Use this to do transfer learning

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When you get to the end of the instructions, you are done with that module. You can then close the digitis tab and this module tabDo NOT close the original Deep Neural Networks tabReturn to the original Deep Neural Networks tab

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When you get to the original Deep Neural Networks tab, click Stop task, and continue to end of page,.

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When you get to the end of page, click Next and continue to the next module

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For Each Module• Step through the slides• Scroll down• Click “start” to launch a GPU session• When ready, click “launch”• This opens a new window for a new module…you go

back and forth between tabs• This new module will have you open DIGITS, creating a

third window…you can go back and forth between all three tabs

• When done with module, hit “stop task”• And continue to bottom of page• Close module and Digits windows, then click Next…

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For More Information:Raymond W. PtuchaAssistant Professor, Computer EngineeringDirector, Machine Intelligence LaboratoryRochester Institute of Technology

Email: rwpeec@rit.eduPhone: +1 (585) 797-5561Office: GLE (09) 3441

http://www.rit.edu/mil