Self-training: F(x,y) is a filtering/ranking function, eg., what we call a reward/return. The input x may be chosen by humans, but the model generates the y’s and F ranks and selects for further rounds of self-training. F can be explicit or implicit (human in the loop as in RLHF)
DATA
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AirByte Loader enables data integration for LangChain applications
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As the final days of #chatyourdata challenge approach, we have one last document loader to enable you… AirByte Loader @AirbyteHQ has 100s of data connectors, and now you can easily use them to load data into a format you can use in LangChain Links
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Open Source ChatGPT Alternative Dataset Contribution Initiative
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Tenéis toda la info en este vídeo. Pero el TL;DR es que estamos contribuyendo al dataset de un futuro asistente similar a ChatGPT que sea open source. Más datos de calidad Mejor rendimiento. Así que cualquier difusión y ayuda será bienvenida 🙂 https://
youtube.com/watch?v=XYT1Tx
INbuM&ab_channel=DotCSV
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AI Today Podcast: Pattern Recognition Definition and Importance
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In this @Cognilytica #AIToday #podcast AI Glossary Series episode 'Pattern Recognition' hosts @rschmelzer & @kath0134 define the term #PatternRecognition, explain how it relates to #AI, and why it’s important to know about. Full episode: https://
aidatatoday.com/ai-today-podca
st-ai-glossary-series-pattern-recognition/?utm_source=dlvr.it&utm_medium=twitter
…
#data #ML #tech -
Aspect-based Sentiment Analysis: Modeling Approaches and Techniques
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Aspect-based sentiment is stuff like “service: good, food: bad”. Sometimes you can model it as multiple label vectors on the text, other times it’s more like spancat or relation extraction
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Data Engineering vs Data Science: Infrastructure and Analysis
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Data Engineering deals with the practical aspects of collecting, storing, & processing large amounts of data, while Data Science involves using that data to build models and make data-driven decisions. Simply put, DE focuses on the infrastructure while DS focuses on the analysis.
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Data Engineering: The Essential Foundation for Data Science
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All paths to Data Science leads through Data Engineering.
— Shubham Saboo (@Saboo_Shubham_) 11 février 2023
Credits: @christianbdata pic.twitter.com/BgtB2T3SAIAll paths to Data Science leads through Data Engineering. Credits: @christianbdata
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Top 6 Business Intelligence Tools for 2023 Data Analysis
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Stay ahead of the game in 2023 with these top 6 business intelligence tools! Enhance your data analysis, decision-making skills & more. Read more about the best BI tools for 2023: https://
bit.ly/3HMpHPw @jeevprabnivash @YellowfinBI @Pentaho @qlik @Infor @Domotalk -
Model Reprogramming for Private Machine Learning
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Awesome meeting Huzaifa! He did some really interesting work showing that model reprogramming can sometimes perform fine tuning for private ML. Check it out: https://
x.com/NicolasPaperno
t/status/1624118654278172692
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Data Oriented Architectures arXiv Paper Feedback Request
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We would love input and feedback on this arXiv paper on Data Oriented Architectures from the AutoAI team here in Cambridge. https://
arxiv.org/abs/2302.04810