First step: Create a #Lakehouse that your organization trusts & utilizes Second step: Use @census
’s reverse ETL to deliver trustworthy data and insight from Databricks to all the tools used by your sales, marketing & ops teams Learn how
TOOLS
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Build Trusted Lakehouse Deliver Data Insights Census
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GPT Implementation in 60 Lines of NumPy and JAX
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Late to the party but "GPT in 60 Lines of NumPy" / picoGPT is nicely done: https://
jaykmody.com/blog/gpt-from-
scratch/
…
– good supporting links/pointers
– flexes some of the benefits of JAX: 1) trivial to port numpy -> jax.numpy, 2) get gradients, 3) batch with jax.vmap
– inferences gpt-2 checkpoints -
Helpful Links for Trending ML Projects and Papers
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helpful links i am aware of for trending projects:
1. papers: https://
papers.labml.ai/papers/weekly
2. papers+code: https://
paperswithcode.com
3. code: https://
github.com/trending -

TIMM Joins Hugging Face: 500 Models and Growing
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timm, welcome to Hugging Face: https://
github.com/huggingface/py
torch-image-models
… Since @wightmanr joined the team in June, a lot has happened. We're closing in on 500 models on the HF Hub, and the docs live at https://
huggingface.co/docs/timm/index Next Better interop w/ transformers, safetensors, … what else? -
Andrej Karpathy discontinues arxiv-sanity maintenance
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Sad but I just don't have the time to maintain it anymore. It's possible I'll try to build yet another version of a more LLM-powered arxiv-sanity, I have a few ideas there. For now it is what it is sorry. Please refer to:
1 https://
papers.labml.ai/papers/weekly
2 https://
paperswithcode.com -
Kangas Open Source Project Installation and GitHub Support
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Kangas is Open Source. You can install and get started with just a few lines of code. Check this and support the project by giving it a star
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Load and Render Pandas DataFrames with Kangas Viewer
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All you want to do is just load a Pandas Data Frame and render it within the Kangas Viewer directly from Python: It also also supports CSVs, DataGrid Files, and even you can manually create a new DataGrid: Here is the code example:
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Kangas: Explore and Visualize Large-Scale Multimedia Data
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Introducing Kangas a Tool that lets you explore, analyze, and visualize large-scale multimedia data 🚀
— Sumanth (@Sumanth_077) 20 février 2023
It also provides you with an intuitive visual interface for performing complex queries on your dataset.
Check this out: 👇 pic.twitter.com/gNm35N7eZBIntroducing Kangas a Tool that lets you explore, analyze, and visualize large-scale multimedia data It also provides you with an intuitive visual interface for performing complex queries on your dataset. Check this out:
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Open Source Tool for Machine Learning Dataset Analysis and Exploration
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In Machine Learning you will be working with a lot of datasets but Analyzing and Exploring datasets is always a mess. Here is an Open Source tool that lets you display and analyze large and multimedia datasets with a few lines of code. Thread
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Generative AI enhances existing skills rather than providing new knowledge
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As @mmitchell_ai said to me, in the best applications of generative AI that she has seen, the tools are not informing people about what they don’t know but helping them do what they do better.