Lauren Neal's repositories
generative-art-node
Create generative art by using the canvas api and node js
long_stable_diffusion
Long-form text-to-images generation, using a pipeline of deep generative models (GPT-3 and Stable Diffusion)
ml-art-colabs
A list of Machine Learning Art Colabs
academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
CLIP
Contrastive Language-Image Pretraining
COVID19_tracker_data_extraction
Data is often not collected by Black communities when it is needed the most. We have compiled a list of all of the states that have shared data on COVID-19 infections and deaths by race and those who have not. This effort is to extract this data from websites to track disparities COVID-19 deaths and cases for Black people.
database_sandbox
resources for working with databases and SQL
DS-3001
DS 3001: Practice of Data Science
ETA
Exploratory Text Analytics
git-novice
Version Control with Git
Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow
Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron
hashlips_art_engine
HashLips Art Engine is a tool used to create multiple different instances of artworks based on provided layers.
laurenneal.github.io
"Under the Influencer" website
metaplex
Protocol and application framework for decentralized NFT minting, storefronts, and sales.
nft-art-generator
A tool to generate generative NFT art projects.
python-intro
uva library workshop on introduction to python
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
r4ds
R for data science: a book
shot-type-classifier
Detecting cinema shot types using a ResNet-50
text-analytics-with-python
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.