Outline:

• Overview

  • "Who even is this guy?"
  • Getting to know your computer
  • Projects to Production
  • AWS (time permitting)
  • Questions

• Who Even Is This Guy?

• Bio

  • High School
    • Aerospace Engineering
    • Jazz Guitar
  • Virginia Commonwealth University
    • Political Science
    • Philosophy
  • Fairfax Hyundai and Kia
    • Customer Relations Manager
  • Center for the Study of Neuroeconomics at George Mason University
    • Research Fellow
    • PhD Student

• What About Now?

  • General Assembly/Booz Allen Hamilton DataScience5k
  • Contract Work
    • MainStreet Bank
    • Rosy
    • ???
  • Research Interests:
    • Computer Vision
    • Adversarial Models
    • Hierarchical Memory Models
    • Neural Computing

Getting To Know Your Computer

• The File System

  • Root vs. Home Directories
  • Finding a place for all your projects
  • Organization

• Interacting with Terminal

  • Basic Commands
    • cd
    • ls, ls -a
    • mv
    • cp
  • vim

• Editing Your bash profile

  • Customizing things so to make your life easier
  • aliasing (quick paths to desktop and jupyter notebooks)
  • formatting/prettifying (find link!)

• Quick anaconda diatribe

  • I don't like anaconda...
  • Homebrew
  • xcode

How to turn your work into a deliverable

• Project vs. Package

  • Projects are single purpose collections of code that should be easily run by an end user, no matter their level of technical expertise.
  • Packages are tools that can be integrated into other projects, and will be used by developers

• Packages

  • Clone this project into your repo/ directory: cifar-extender

• cifar-extender

  • Structure
    • setup.py
    • requirements.txt
    • README.md
    • LICENSE.txt
    • your_package/
    • main.py/main.sh

• setup.py

  • Provides an overview of your package, that is used for classification/tagging purposes

• requirements.txt

  • A listing of the packages that are needed to run your code

• README.md

  • A human-readable description of your package, and provides a description on its use

• LICESNSE.txt

  • Provides legal protection for your work, and describes its appropriate use and reuse by others
  • OSI
  • Common Licenses
    • BSD 2/3 Clause
    • MIT
    • Apache

• your-package/

• This is where you will put all of your code

• Should contain the file __init__.py

• main.py/demo.sh

  • this is the package level script that will execute your code

• Projects

  • Clone this project into your repo/ directory: 'tf-retrainer'

• tf-retrainer

  • Project for retraining an Inception Net model on your own image data
  • Uses the TensorFlow transfer learning API
  • Allows you to create a custom image classification model

• Computer Vision Digression

  • Algorithms for performing tasks with image data
  • Common tasks
    • Image classification
    • Object detection
  • Typically done with Convolutional Neural Networks

• Transfer Learning Digression

  • The models that are trained are often incredibly deep, and are trained with massive datasets
  • Shameless Plug: cifar-image-classifier
  • Many of the complex features rely on the same fundamental features, so they can be used for a wide variety of tasks
  • Transfer learning enables you to retrain the final layers of a model to use the pre-trained knowledge

• Running tf-retrainer

  • We'll run the transfer learning model on the images curated by cifar-extender