With support for new expressions, our built-in H3 capabilities are becoming best-in-class Learn how can make your queries more efficient and expressions more flexible
AI
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Start Contributing to Open Source Tools You Use Daily
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No need to be above mentioned projects. Think of the tools and libraries you are working on daily within your projects and start contributing to that. For example Pandas, Numpy, Matplotlib, Tensorflow, Jax, etc. It can be of any project just start contributing to Open Source.
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Open-source ML Tools Content Series Coming Soon
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That's it. Hope you enjoyed reading this. I will be sharing more content on all open-source ML Tools in the coming threads. Follow me @Sumanth_077 so won't miss what's coming next.
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Bento ML: Open Source Framework for Production ML Models
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7. Bento ML It is an open source model serving framework that helps you take your ML Models to Production https://
github.com/bentoml/ -
Lightning AI: Build and Deploy AI Models Without Infrastructure Worries
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6. Lightning AI This helps you build AI products, train, finetune and deploy models on the cloud without worrying about infrastructure, cost management. https://
github.com/Lightning-AI/l
ightning
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ZenML: Open-Source ML Pipeline Framework Integration Tool
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5. ZenML Open-source pipeline framework that integrates all your ML tools https://
github.com/zenml-io/zenml -
Deepchecks: Python Package for ML Model and Data Validation
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4. Deepchecks Deep checks is a Python package for comprehensively validating your machine learning models and data with minimal effort. https://
github.com/deepchecks/dee
pchecks
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MindsDB: AI Layer for Databases with SQL-Based ML Models
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2. Mindsdb MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning models using SQL queries.
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Weights & Biases: MLOps Platform for Model Development
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3. Weights & Biases Mlops Platform to build better models faster with experiment tracking, dataset versioning, and model management https://
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Hugging Face: ML Platform for Building Training and Deploying Models
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1. Hugging Face No Introduction require for Hugging Face if you are in ML Space. It is a community and data science platform that provides Tools that enable users to build, train and deploy ML models based on open-source code and technologies. https://
github.com/huggingface/tr
ansformers
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