- Versioning Machine Learning Experiments vs Tracking Them - Dec 27, 2021.
Learn how to improve ML reproducibility by treating experiments as code.
Experimentation, Machine Learning, Version Control
- GitHub Desktop for Data Scientists - Sep 29, 2021.
Less scary than version control in the command line.
Data Science, Data Scientist, GitHub, Version Control
- ModelDB 2.0 is here! - Mar 19, 2020.
We are excited to announce that ModelDB 2.0 is now available! We have learned a lot since building ModelDB 1.0, so we decided to rebuild from the ground up.
MLOps, ModelDB, Modeling, Version Control
- Automatic Version Control for Data Scientists - Sep 24, 2019.
How can you keep your machine learning models and data organized so you can collaborate effectively? Discover this new tool set available for better version control designed for the data scientist workflow.
Data Scientist, GitHub, Jupyter, Version Control
- Version Control for Data Science: Tracking Machine Learning Models and Datasets - Sep 13, 2019.
I am a Git god, why do I need another version control system for Machine Learning Projects?
Data Science, Datasets, Machine Learning, Modeling, Version Control
- DevOps for Data Scientists: Taming the Unicorn - Jul 27, 2018.
How do we version control the model and add it to an app? How will people interact with our website based on the outcome? How will it scale!?
Data Science, Data Scientist, DevOps, Unicorn, Version Control
- How A Data Scientist Can Improve Productivity - May 25, 2017.
Data Science projects involve iterative processes and may need changes in data at every iteration. But Data versioning, data pipelines and data workflows make Data Scientist’s life easy, let’s see how.
CRISP-DM, Data Scientist, Data Workflow, DVC, GitHub, Version Control
- Data Version Control: iterative machine learning - May 11, 2017.
ML modeling is an iterative process and it is extremely important to keep track of all the steps and dependencies between code and data. New open-source tool helps you do that.
CRISP-DM, DVC, GitHub, Machine Learning, Open Source, Reproducibility, Version Control
