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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@sumanth_077
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Lightning AI: Build and Deploy AI Models Without Infrastructure Worries
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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://
github.com/wandb/wandb -
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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Open Source Guide: Contributions, Career Growth, and Non-Code Roles
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If you are new and don't know about open source. Here is the Podcast that will help you understand 1. What is Open Source?
2. How to Contribute to Open Source?
3. What are some Non-Code Contributions?
4. How open source can help you in your career? -
7 Open Source Machine Learning Startups for Job Seekers
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If you are into Machine Learning and looking for a Job? The best way to showcase your Tech and Non-Tech skills to a recruiter is by contributing to Open Source. Here's a list of 7 Open Source Machine Learning Startups that you can contribute to
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Appreciation for Well-Written COT Prompting Article
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An interesting read on COT Prompting, well-written Shubham
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Pandera: Python Library for Pandas DataFrame Validation
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Validate your Pandas DataFrame with "Pandera". In a Data Science Project testing the data is important to make sure that it works as you expected. Here is an amazing python library that helps you in data validation.