Hi, I'm Jon 🧑🏻‍💻🎄

notebook about vectorization with Gensim + Word2Vec and sentiment analysis with BERT + BART

splitting text up with tokenization + removing "textual noise" + reducing tokens with stemming and lemmatization

notebook about NLP and frequency-based vectorization methods (bag of words + TF/IDF)

glossing over ways how "things" can learn about words

third notebook about machine learning (clustering and connecting to an LLM)

second notebook about machine learning (another case study + multiple linear regression)

first notebook about machine learning (supervised + unsupervised) with case study and exercise

glossing over the many ways a thing can learn

providing mathematical functions for the Python programmer

notebook about data transformation and model building

using add-ons for Python : installing + importing + programming

summarizing an exercise in matrix data manipulation

a next.js front-end for the sanity back-end

displaying tables with datasets from Google Sheets

mashing up a user-customizable tech-centric news syndicator