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blog

Repository that hosts my blog (created using fastpages)

dash-tabs

Example of how to use tabs in a plotly's Dash framework across multiple files

dash_oop_components

OOP components for plotly dash that make dashboard components composable, reusable and configurable

dash_oop_demo

Deployment example of dash_oop_components library

dash_querystrings

Example of how to include querystrings to save state url in plotly's Dash

dashboard_test

deploy-xgboost-to-aws-lambda

short guide on how to deploy xgboost machine learning models to production on AWS lambda

dtreeviz

A python library for decision tree visualization and model interpretation.

explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

explainerdashboard-feedstock

A conda-smithy repository for explainerdashboard.

explainingtitanic

A demonstration of the explainerdashboard package that that displays model quality, permutation importances, SHAP values and interactions, and individual trees for sklearn RandomForestClassifiers, etc

fastai

The fastai deep learning library, plus lessons and tutorials

flask-simplelogin

Simple Login - Login Extension for Flask - maintainer @cuducos

go-hello

repo to experiment with golang

hello-github-actions

keras-embeddings

Example of how to use entity embeddings (similar to word embeddings such as word2vec, but then generalized for any categorical feature) in a Keras model.

langchain

⚡ Building applications with LLMs through composability ⚡

name-matching-in-python

Surprisingly Effective Way To Name Matching In Python These are the same product name and customer name but were taken as different form i.e., deal with different versions of one name.

oegedijk

pdpbox

python partial dependence plot toolbox

pytest-actions

repo to debug github actions error where pytest generates 127 error

python-datascience-course

notebooks for internal Python for Datascience course that I teach at UWV.

readme-with-video

rule_estimator

A scikit-learn compatible estimator based on business-rules with interactive dashboard included

ruledashboarddemo

demo deployed to heroku of the rule-estimator dashboard

sagemaker-creditscore-explainer

Example of how to deploy an ML algorithm together with SHAP explanations to AWS Sagemaker, including a front end dashboard.

sklearn-transformers

A collection of sklearn compatible transformer classes. Sklearn's standard transformers have some annoying lacunes (especially when fitting on new data with labels missing in training data for example), so these transformers fix that. Also some other more adventurous transformer classes. Shows how to quickly make transformer pipelines for e.g. making dataframe ready for neural net with embeddings.

sparse_dot_topn

Python package to accelerate the sparse matrix multiplication and top-n similarity selection