Clean data is the biggest MOAT, in the age of AI! LLM finetuning datasets often contain bad examples, which are harder to detect manually & become a major performance blocker. But there's a solution:
@akshay_pachaar
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Python ML/MLOps Expert Shares AI Engineering Newsletter
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If you interested in: – Python – ML/MLOps – LLMs – AI Engineering Find me → @akshay_pachaar I also write a FREE weekly Newsletter @ML_Spring on AI Engineering!
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RAG Evaluation: Building and Assessing Retrieval Augmented Generation
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Building RAG is not enough, you also need evaluate it! I recently published a @LightningAI Studio on RAG evaluation! Check this out
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Python Machine Learning and AI Engineering Resources
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If you interested in: – Python – Machine Learning – AI Engineering Find me →
@akshay_pachaar My Newsletter on AI Engineering → @ML_Spring Cheers! -
U-Net Semantic Segmentation Library Released
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How it works Internally it uses a U-Net based foreground/background semantic segmentation and yields the post processed results. If you try it, library would download the trained model first. Fine the code here:
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Python Library Removes Image Backgrounds in Five Lines
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This Python library is so powerful! Remove Background of an Image in just 5 lines of code! Try yourself!
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Automatic Error Detection in Tabular Enterprise Data
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Automatically detect errors in any tabular dataset! Despite the flashy allure of GenAI, 90% of the data that drives enterprise businesses is still tabular & it's poor-quality is costing trillions of $ every year. As we dive into the era of big data, the focus often shifts to
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Python Machine Learning and AI Engineering Resources
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If you interested in: – Python – Machine Learning – AI Engineering Find me →
@akshay_pachaar
My Newsletter on AI Engineering → @ML_Spring Cheers!
