iterative / ldb-resources
☆28Updated 2 years ago
Alternatives and similar repositories for ldb-resources:
Users that are interested in ldb-resources are comparing it to the libraries listed below
- Benchmarks for DVC☆20Updated last week
- DVC's data management subsystem☆18Updated last week
- Data and tooling to compare the API surfaces of various array libraries.☆54Updated 2 months ago
- A use case of a reproducible machine learning pipeline using Dask, DVC, and MLflow.☆23Updated 5 years ago
- Extension to hypothesis for testing numpy general universal functions☆39Updated 4 years ago
- 📈 Log and track ML metrics, parameters, models with Git and/or DVC☆172Updated last week
- Dvc + Streamlit = ❤️☆40Updated last year
- Dataset registry DVC project☆74Updated 11 months ago
- Interactive parametric benchmarks in Python☆17Updated 4 years ago
- 🏷️ Git Tag Ops. Turn your Git repository into Artifact Registry or Model Registry.☆146Updated last week
- yogadl, the flexible data layer☆74Updated 2 years ago
- ☆30Updated 3 years ago
- Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production…☆29Updated last year
- dask-pytorch-ddp is a Python package that makes it easy to train PyTorch models on dask clusters using distributed data parallel.☆59Updated 4 years ago
- A library to instantiate any Python object from configuration files.☆24Updated 2 years ago
- Using MLflow with a PostgreSQL Database Tracking URI and a Minio Artifact URI, and MLflow Registry☆12Updated 4 years ago
- ☆18Updated 3 years ago
- Generate beautiful, testable documentation with Jupyter Notebooks☆21Updated 2 years ago
- Unified Distributed Execution☆52Updated 6 months ago
- ☆17Updated last year
- Synchronicity lets you interoperate with asynchronous Python APIs.☆108Updated 3 weeks ago
- A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-…☆67Updated last year
- Listens MLFlow model registry changes and deploy models based on configurations☆21Updated last year
- Scale Optuna with Dask☆35Updated 4 years ago
- Tries to shrink your Pandas column dtypes with no data loss so you have more spare RAM☆84Updated last year
- Kedro-Accelerator speeds up pipelines by parallelizing I/O in the background.☆35Updated 3 years ago
- ☆20Updated 2 years ago
- Automate issue discovery for your projects against Lightning nightly and releases.☆47Updated last week
- ☁️ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.☆45Updated last month
- Build a conda package from a setuptools project☆32Updated 5 months ago