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Documents Build an Anti-Troll Bot Using TensorFlow and Arduino -- Episode 453
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  • Author Author: tariq.ahmad
  • Date Created: 2 Jul 2020 2:29 PM Date Created
  • Last Updated Last Updated: 3 Jul 2020 7:24 AM
  • Views 2315 views
  • Likes 10 likes
  • Comments 6 comments
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Build an Anti-Troll Bot Using TensorFlow and Arduino -- Episode 453

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Andy hooks up a USB Keyboard to a Microcontroller to see he can use machine learning to do a critique of his internet comments. Challenges included flashing the firmware of the FTDI module, analysis of USB Human Input Device (HID) data and running a machine learning algorithm on a 32bit Arm M0 core.

Supplemental Content:

  • USB Keyboard / HID
  • VNC2 - Getting to Blink
  • SPI Slave on an Arduino MKR Zero
  • Using a hash function Tokenization during Text Classification on memory constrained devices

Bill of Material:

Product Name Manufacturer Quantity Buy Kit
VNC2-48Q USB HOST Control FTDI 1 Buy Now
VNC2 Debugger/Programmer FTDI 1 Buy Now
Development Board, Arduino MKR Zero ARDUINO 1 Buy Now
DC Servo Motor, 6 V AdaFruit 1 Buy Now

 

Additional Parts:

 

Product Name

Jumbo sized googlie eyes

PETG 3D printer filament

MDF board

Paint

image
Build an Anti-Troll Bot Using TensorFlow and Arduino

element14 Presents  |  About Workshopshed  |  Project Videos

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Top Comments

  • DAB
    DAB over 3 years ago +3
    An interesting build. I could be useful during those moments when your passion overwhelms your desire to restrain your comments. DAB
  • ralphjy
    ralphjy over 3 years ago +3
    Interesting application. I can think of a few people who could use one. Nice to see TinyML in action.
  • Workshopshed
    Workshopshed over 3 years ago +3
    Here's some of the reference material I used for those wanting to reproduce this experiment. https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/overview https://www.aclweb.org/anthology…
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  • Workshopshed
    Workshopshed over 3 years ago

    Here's some of the reference material I used for those wanting to reproduce this experiment.

     

    • https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/overview
    • https://www.aclweb.org/anthology/W18-5105/
    • https://github.com/iampukar/toxic-comments-classification
    • https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6837517.pdf

     

    I would recommend using one of the Tensor Flow Lite supported boards such as the Arduino Nano 33 BLE Sense as the MKR Zero gave me extra challenges because the libraries had not been ported for that platform.

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  • Workshopshed
    Workshopshed over 3 years ago

    Here's some of the reference material I used for those wanting to reproduce this experiment.

     

    • https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/overview
    • https://www.aclweb.org/anthology/W18-5105/
    • https://github.com/iampukar/toxic-comments-classification
    • https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6837517.pdf

     

    I would recommend using one of the Tensor Flow Lite supported boards such as the Arduino Nano 33 BLE Sense as the MKR Zero gave me extra challenges because the libraries had not been ported for that platform.

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    • Vote Up +3 Vote Down
    • Sign in to reply
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