DIY AI: ML5 Community Starter Kit

A beginner's guide to machine learning for making text-generating AI bots. Centering the needs of communities interested in working with their own texts, archives, and “small data”.

import machinelearnntoolkit
def codingtutorials(🐬):
'build a poetry bot with ML5 and charRNN)'
'build a chatbot with GPT2 and Runway ML)'
def webscrapingtutorials(🐬):
'create your own datasets using simple web scrapers–
no coding knowledge required'
def datasettutorials(🐬):
'ethical guidelines and resources for working with datasets–
finding, vetting, cleaning, documenting'
def glossary(🐬):
'list of terms demystifying machine learning jargon and tools,
like tensorflow, seq2seq, word2vec, etc'
def visualaids(🐬):
'cute simple diagrams illustrating how language models work
(RNNs, CNNs, LSTMs, GPT-2, BERT, etc.)'
def resources(🐬):
'compiling and amplifying complimentary ML guides and tools
by other amazing 🐚👁🐍 beings'
Who this?

This project was initiated by Emily Martinez, as part of her ML5.js Fellowship, under the mentorship of Lydia Jessup and Dan Shiffman.

Emily is one of four ML5.js Fellows for 2020, a partnership between Processing Foundation and NYU’s Interactive Telecommunications Program that specifically focuses on ml5.js.

🤓 Read What Can Machine Learning Teach Us About Ourselves?, an interview with Emily Martinez, to learn more.