Sdk Alternatives

Similar projects and alternatives to sdk

• mandala

  8 228 6.3 Python sdk VS mandala

  A powerful and easy to use Python framework for experiment tracking and incremental computing

• pytorch-lightning

  19 19,188 9.9 Python sdk VS pytorch-lightning

  Discontinued Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning] (by PyTorchLightning)

  

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• aim

  70 4,797 8.0 Python sdk VS aim

  Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

  

• spaCy

  106 28,789 9.2 Python sdk VS spaCy

  💫 Industrial-strength Natural Language Processing (NLP) in Python

  

• pytorch-lightning

  1 18,249 9.9 Python sdk VS pytorch-lightning

  Discontinued The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. [Moved to: https://github.com/PyTorchLightning/pytorch-lightning] (by williamFalcon)

  

• pytorch-lightning

  9 26,952 9.9 Python sdk VS pytorch-lightning

  Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

  

• mlrun

  3 1,301 9.9 Python sdk VS mlrun

  MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.

  

• SaaSHub

  www.saashub.com featured

  SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

  

• Kedro

  29 9,362 9.7 Python sdk VS Kedro

  Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.