Reproducibility Session List

Talk pydata-pydata-scientific-libraries-stack

Flexible ML Experiment Tracking System for Python Coders with DVC and Streamlit

Antoine Toubhans

Best Practice, Computer Vision, Data Engineering, Data Visualization, Development Methods, Reproducibility

Flexible ML Experiment Tracking System for Python Coders with DVC and Streamlit

Tutorial general-production

Introduction to MLOps with MLflow

Tobias Sterbak

Best Practice, Predictive Modelling, Reproducibility

Learn the basics of MLops with MLflow to manage the machine learning life-cycle.

Talk pydata-jupyter

JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python

Jeremy Tuloup

Jupyter, Reproducibility, Use Case

JupyterLite is a Jupyter distribution that runs entirely in the web browser, backed by in-browser language kernels such as the WebAssembly powered Pyodide kernel. JupyterLite enables data science and interactive computing with the PyData scientific stack, directly in the browser.

Tutorial pydata-machine-learning-stats

Making MLOps uncool again

David

Best Practice, Development Methods, Reproducibility

In this workshop, we will learn what it means and how to build an "MLOps workflow" by extending the power of Git and GitHub with open-source tools.

Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains Datalore Team

Alena Guzharina

Data Visualization, Jupyter, Reproducibility

Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains @Datalore Team Join our talk to discuss setting up environments, working with data, writing code without IDE support, and sharing results, as well as collaboration and reproducibility.