JungeAlexander
Startup CTO and Co-founder @amass-technologies | Biomedical data scientist.
amass technologiesCopenhagen, Denmark
Pinned Repositories
bioinf-tools
A collection of tools useful in everyday bioinformatics workflows.
cocoscore
CoCoScore: context-aware co-occurrence scores for text mining applications
finstar-pipelines
🚧 WIP: collecting financial data
fitbit-data
Analyzing and visualizing my Fitbit data
kbase
kbase - work in progress
kbase_db_api
langdev
py310_new_features
🚧 WIP: An exploration of new features in Python 3.10.
rr
recommended reading
JungeAlexander's Repositories
JungeAlexander/rr
recommended reading
JungeAlexander/kaggle-nbme-score-clinical-patient-notes
JungeAlexander/alexanderjunge.net
JungeAlexander/aoai-realtime-audio-sdk
Azure OpenAI code resources for using gpt-4o-realtime capabilities.
JungeAlexander/azureml-demo
🚧 WIP: An non-exhaustive exploration of AzureML features.
JungeAlexander/base-env
JungeAlexander/blogdown_website
JungeAlexander/demo-docker-compose
JungeAlexander/great-expectations-tutorial
JungeAlexander/handson-ml2
JungeAlexander/instructor-search-metadata-demo
Demo using instructor to extract metadata from search queries
JungeAlexander/JungeAlexander
JungeAlexander/JungeAlexander.github.io
JungeAlexander/kaggle-uspppm
JungeAlexander/lost-text-cat
JungeAlexander/nbdev
Create delightful python projects using Jupyter Notebooks
JungeAlexander/nextjs-tutorial
JungeAlexander/notebooks
Jupyter notebooks for the Natural Language Processing with Transformers book
JungeAlexander/openai_realtime_client
A simple client and utils for interacting with OpenAI's Realtime API in Python
JungeAlexander/overlord
Official pytorch implementation of "Scaling-up Disentanglement for Image Translation", ICCV 2021.
JungeAlexander/personal_health
JungeAlexander/prefect-tutorial
JungeAlexander/pyscript-demo
Pyscript demo and example repository
JungeAlexander/qself
Tools to extract personal, quantitative data from various sources.
JungeAlexander/qself-assistant
JungeAlexander/ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.
JungeAlexander/ray-serve-demo
Taking Ray Serve for a spin.
JungeAlexander/tensorflow-2-public
JungeAlexander/uspppm-demo
Code underlying the Hugging Face Space jungealexander/uspppm-demo
JungeAlexander/zenml-test