Name: Deep Learning - Computer Vision - Classification using CNN - Hands-on workshop
Start: 2018-11-06T19:00:00-05:00
End: 2018-11-06T21:00:00-05:00
Location: Princeton University - Lewis Library Rm 120

Goal: To learn and apply deep learning techniques to computer vision

Roadmap: The following techniques will be covered in 4 different sessions
1) Classification
2) Object detection
3) Object localization
4) Instance Segmentation

Agenda - 1st session
a) What are Convolutional Neural Networks (CNN)?
b) How does classification work in a CNN?
c) Hands-on workshop for classification

Speaker: Anand Kadumberi, Data Scientist

Environment setup

https://www.linkedin.com/pulse/setting-up-python-environment-data-science-machine-keras-kadumberi/

Pre-requisites:

1. Elementary proficiency in python.
2. A system with GPU (cloud/laptop/desktop) for hands-on workshop
3. Software – Anaconda 3, tensorflow-gpu, keras, opencv-python, jupyter lab

Tutorial or Books recommended

1. Standford lectures - Convolutional Neural Networks for Visual Recognition (https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv).

2. Deep learning (Ian Goodfellow)

3. Deep learning with python (Francois Chollet)

Prasad Sripathi

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Deep Learning - Computer Vision - Classification using CNN - Hands-on workshop

Princeton University - Lewis Library Rm 120

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Deep Learning - Computer Vision - Classification using CNN - Hands-on workshop

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