uber / petastormLinks
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
☆1,849Updated last week
Alternatives and similar repositories for petastorm
Users that are interested in petastorm are comparing it to the libraries listed below
Sorting:
- A low-latency prediction-serving system☆1,420Updated 4 years ago
- Open Source ML Model Versioning, Metadata, and Experiment Management☆1,732Updated last year
- Library for exploring and validating machine learning data☆773Updated last month
- MLeap: Deploy ML Pipelines to Production☆1,518Updated 8 months ago
- TFX is an end-to-end platform for deploying production ML pipelines☆2,155Updated last month
- Hopsworks - Data-Intensive AI platform with a Feature Store☆1,242Updated 6 months ago
- Distributed Computing for AI Made Simple☆1,047Updated 2 years ago
- For recording and retrieving metadata associated with ML developer and data scientist workflows.☆654Updated 4 months ago
- Automated Machine Learning on Kubernetes☆1,615Updated this week
- NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale da…☆1,095Updated 11 months ago
- Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO☆732Updated this week
- Universal model exchange and serialization format for decision tree forests☆780Updated last week
- A model-agnostic visual debugging tool for machine learning☆1,669Updated 6 months ago
- Train and run Pytorch models on Apache Spark.☆339Updated 2 years ago
- Model analysis tools for TensorFlow☆1,270Updated last week
- Scalable Machine Learning with Dask☆942Updated 3 months ago
- Hummingbird compiles trained ML models into tensor computation for faster inference.☆3,456Updated 3 weeks ago
- Input pipeline framework☆986Updated this week
- PyTorch elastic training☆729Updated 3 years ago
- A uniform interface to run deep learning models from multiple frameworks☆939Updated last year
- Experiment tracking, ML developer tools☆887Updated 3 months ago
- Kubeflow’s superfood for Data Scientists☆639Updated this week
- TonY is a framework to natively run deep learning frameworks on Apache Hadoop.☆707Updated last year
- High performance model preprocessing library on PyTorch☆648Updated last year
- An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models☆4,601Updated this week
- The Open Source Feature Store for AI/ML☆6,246Updated this week
- Jupyter magics and kernels for working with remote Spark clusters☆1,357Updated last month
- TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows…☆2,266Updated last year
- MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle☆3,661Updated last week
- Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.☆2,738Updated last year