Name: Daniel Kapitan
Type: User
Company: freelance data scientist
Bio: Physicist-turned-data-scientist. Helping others to do more with data. Connecting machine learning with self-organisation. Pythonista.
Location: Rotterdam, the Netherlands
Blog: https://linkedin.com/in/dkapitan
Daniel Kapitan's Projects
SQLAlchemy driver for DuckDB
Slides for a forecasting course based on "Forecasting: Principles and Practice"
Business intelligence as code: build polished data products with SQL and markdown
Case study of Dutch WMO voorspelmodel
Training program generator using Jack Daniels' Running Formula
Feedzai's theme for Altair charts.
FHIR-PYrate is a package that provides a high-level API to query FHIR Servers for bundles of resources and return the structured information as pandas DataFrames. It can also be used to filter resources using RegEx and SpaCy and download DICOM studies and series.
FHIR Resources https://www.hl7.org/fhir/resourcelist.html
Data vault creation of general clinical data. Based upon the python pyelt framework.
Template for simple Python Google Cloud Function
A collection of useful .gitignore templates
Hands-On Graph Neural Networks Using Python, published by Packt
Focusing on the generalization of concepts, functionality, and overall processes involved in the creation of a secure 'network of trusted data' , the IDS-RAM resides at a higher abstraction level than common architecture models of concrete software solutions do. The document provides an overview and dedicated architecture specifications.
The Information Model of the International Data Spaces implements the IDS reference architecture as an extensible, machine readable and technology independent data model.
Fit interpretable models. Explain blackbox machine learning.
Book about interpretable machine learning
Interactive Canvas in Jupyter
Porting the R code in ISL to python. Labs and exercises
ISLP package: data and code for labs
Up-to-date version of labs for ISLP
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
In-company cases of JADS PE level 2 participants
Working paper for developing new Knowledge Science curriculum
Generative art with L-systems
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Course material from SuperDataScience
A set of notebooks used in the Data Science & AI professional education courses