Hugging Face Fellows is a network of exceptional people from different backgrounds who contribute to open-source machine learning See what our Fellows have accomplished this month, in the inaugural edition of Fellows Highlights https://
huggingface2.notion.site/Hugging-Face-F
ellows-Highlights-March-8-2023-2def41320c144c57a8091ff77f880bcf
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EDUCATION
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Hugging Face Fellows Highlights: Open-Source ML Contributions
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Daily Python and Machine Learning Concepts Sharing Wrap-up
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That's a wrap. Every day, I share and simplify complex concepts around Python, Machine Learning & Language Models. Follow me → @Sumanth_077 if you haven't already to ensure you don't miss that. Like/RT the first tweet to support my work and help this reach more people
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Kaggle: Free Datasets for Data Science Projects
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1. Kaggle No Introduction is required to kaggle, you can find 1000's datasets which you can download and use for free Check it out here: https://
kaggle.com/datasets -

More Effective Vocabulary Learning Method Using ChatGPT
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a more effective way to learn vocab words than straight memorization with ChatGPT
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Learn LLMs and Build Auto-Summarising Bot in 4 Hours
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Replit is the fastest way to get started with generative AI, and now our friends at @AICampOfficial bring a new course to teach you all about LLMs. In just 4 hours, you'll learn the powers of GPT3 and end up building your own auto-summarising bot. Genius!
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Recommendation to Start with Made with ML
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made with ml is a good one Prathik, Get started with that
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DeepSparse Project Completion and Data Science Tutorials
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That's a wrap! You can read more about DeepSparse here https://
neuralmagic.com/deepsparse/ Everyday, I share tutorials around Data Science & Machine Learning. You can find me → @Sumanth_077 Like/RT the first tweet to support my work and help this reach more people -
Laura’s UX Designer Journey at MathWorks
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From uncertainty to excitement: check our Laura's journey to becoming a UX designer at MathWorks http://
spr.ly/60153s29S -
AI Research Guide Resource for Students
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This guide is a nice resource for AI research students. https://
arxiv.org/abs/2108.02497 -

Guide to Avoiding Machine Learning Pitfalls for Researchers
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How to avoid machine learning pitfalls: a guide for academic researchers A really nice guide on doing machine learning the right way. Covers nearly all machine learning stages(before/after modeling, evaluation,…) and do's & don'ts in each stage. https://
arxiv.org/abs/2108.02497