This week we have a fantastic report on the use of Large Language Models and an opportunity for you to take part in the Data Maturity Survey 2025. ⏬ Check it out below
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What to Study if you Want to Master LLMs What foundational concepts should you study if you want to understand Large Language Models?Continue reading on Towards Data Science »... https://lnkd.in/e-YXq4jS #AI #ML #Automation
What to Study if you Want to Master LLMs
openexo.com
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Executive and Thought Leadership in "Gen AI", "Machine Learning", "Artificial Intelligence", "Data Science", "Multi-Cloud", "Hybrid Cloud", "AWS", "Azure", Google Cloud", "Data Analytics" "MLOps", "AIOps"
#Technology #DataAnalytics #DataDriven Understanding Buffer of Thoughts (BoT) — Reasoning with Large Language Models: New prompt engineering tool for complex reasoning, compared with Chain of thought (CoT) and Tree of Thought (ToT) Continue reading on Towards Data Science » #MachineLearning #ArtificialIntelligence #DataScience
Understanding Buffer of Thoughts (BoT) — Reasoning with Large Language Models
towardsdatascience.com
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Chief of Staff at causaLens - trying to bring the marginal cost of data science to $0
causal agents? 👀 “while LLMs excel in handling natural language data, creating a structural mismatch that impedes effective reasoning with tabular data. This lack of causal reasoning capability limits the development of LLMs. To address these challenges, we have equipped the LLM with causal tools” reasoning with tabular & time-series data is a different ball game compared to predicting the next word. we are launching some cool agents at our next Causal AI conference in London 👀 👀 👀 register for in person or livestream: https://lnkd.in/dyWnaeMF our objectives are to: A. empower data scientists, quants & economists with productivity tools B. empower non technical users/ domain experts to perform simple data science tasks via a chat interface. (cleaning data, creating dashboards, building simple models etc) this is just the starting point the agents are becoming increasingly accurate & powerful link to the paper: https://lnkd.in/dPqVxsim github repo: https://lnkd.in/dcn5uzAb
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Learn how to solve your most common data warehouse problems in this new guide. Uncover how to: - Use natural language to query data sources - Reduce admin tasks with AI-powered optimization - Scale up performance while controlling cost
A Guide to Data Warehousing in the Lakehouse
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Sentiment Classification: Once the features are extracted, sentiment classification algorithms are used to determine the sentiment conveyed by the text data. Click for more https://bsapp.ai/YW_kCSi-o #MachineLearning
Natural Language Processing (NLP)
kiziridis.com
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Network Administrator and Linux VPS Management | WordPress & SEO Specialist | Cloud and Cyber Security
Scalable Data Labeling Strategies: Integrating Hybrid Approaches and Large Language Models https://lnkd.in/effMPCxb #data #llms #ScalableData
Optimizing Data Labeling with Large Language Models (LLMs)
https://jalalnasser.com
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Learn how to solve your most common data warehouse problems in this new guide. Uncover how to: - Use natural language to query data sources - Reduce admin tasks with AI-powered optimization - Scale up performance while controlling cost
A Guide to Data Warehousing in the Lakehouse
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Retrieval-augmented generation is a technique that can improve the accuracy of Large Language Models. Learn how it works, and how it can benefit large businesses, data analysts, customer service centers, and more in this thoughtful piece by Gino Maulini. https://lnkd.in/gp-3z7XW #RAG, #RetrievalAugmentedGeneration, #LLM, #LargeLanguageModels, #7Rivers
Retrieval-Augmented Generation (RAG) Basics - 7Rivers
https://7riversinc.com
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Databricks | Data Engineering | Data Migration | Data Governance | Spark | Analytics | LLM | AI
Learn how to solve your most common data warehouse problems in this new guide. Uncover how to: - Use natural language to query data sources - Reduce admin tasks with AI-powered optimization - Scale up performance while controlling cost
A Guide to Data Warehousing in the Lakehouse
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Learn how to solve your most common data warehouse problems in this new guide. Uncover how to: - Use natural language to query data sources - Reduce admin tasks with AI-powered optimization - Scale up performance while controlling cost
A Guide to Data Warehousing in the Lakehouse
