python] [ datascience learning machinelearning python career productivity omscs production engineering lazada til business leadership communication agile recsys misc spark nlp deeplearning ]
A step-by-step of how to migrate from json comments to Utterances.
Checking for correct implementation, expected learned behaviour, and satisfactory performance.
Updating our FastAPI app to let users select options and download results.
I couldn't find any guides on serving HTML with FastAPI, thus I wrote this to plug the hole on the internet.
I wanted to add my recent writing to my GitHub Profile README but was too lazy to do manual updates.
After this article, we'll have a workflow of tests and checks that run automatically with each git push.
Automate your experimentation workflow to minimize effort and iterate faster.
Comparing baselines (matrix factorization) against novel approaches using graphs & NLP.
Beating the baseline using Graph & NLP techniques on PyTorch, AUC improvement of ~21% (Part 2 of 2).
Building a baseline recsys based on data scraped off Amazon. Warning - Lots of charts! (Part 1 of 2).
In-depth sharing on how to put machine learning systems into production.
First, start with the simplest solution, and then add intelligence.
Landing rockets (fun!) via deep Q-Learning (and its variants).
Revisiting the fundamentals and learning new techniques.
Performing computer vision tasks with ONLY numpy.
Or how to put machine learning models into production.
A web app to find similar products based on image.
Cleaning up text and messing with ascii (urgh!)
A simple web app to classify fashion images into Amazon categories.
Parsing json and formatting product titles and categories.