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TARNet and Dragonnet: Causal Inference Between S- And T-Learners | by Dr. Robert Kübler | Mar, 2024

Learn how to build neural networks for direct causal inference Photo by Geranimo on UnsplashBuilding machine learning models is fairly easy nowadays, but often, making good predictions is not enough. On top, we want to make causal statements about interventions. Knowing with high accuracy that a customer will leave our company is good, but knowing…

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Visualize your RAG Data — Evaluate your Retrieval-Augmented Generation System with Ragas | by Markus Stoll | Mar, 2024

How to use UMAP dimensionality reduction for Embeddings to show multiple evaluation Questions and their relationships to source documents with Ragas, OpenAI, Langchain and ChromaDB 13 min read · 19 hours ago Retrieval-Augmented Generation (RAG) adds a retrieval step to the workflow of an LLM, enabling it to query relevant data from…

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Impact of Rising Sea Levels on Coastal Residential Real Estate Assets | by Riddhisha Prabhu | Mar, 2024

Using scenario based stress testing to identify medium (2050) and long term (2100) sea level rise risks This project utilizes a scenario based qualitative stress testing approach to identify US coastal census tracts expected to adversely impacted by sea level rise (SLR) in the medium (2050) and long term (2100). One Baseline and two ‘plausible…

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How to Implement ChatGPT with OpenAI API in Python Synchronously and Asynchronously | by Lynn G. Kwong | Mar, 2024

Learn to use AI to boost the efficiency of your business Image by geralt on PixabaySince the advent of ChatGPT, it has brought tremendous shock to human society. Especially for us developers, our lives have been reshaped dramatically because of it. ChatGPT can answer all kinds of technical and non-technical questions correctly, accurately, and efficiently.…

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