Quivr is an open-source RAG framework and a robust AI assistant that helps you manage and interact with information, reducing the burden of information overload. It integrates with all your files and programs, making it easy to find and analyze your data in one place.
Discussion on the efficiency of Random Forest algorithms for PCA and Feature Importance. By Christopher Karg for Towards Data Science.
The paper proposes a two-phase framework called TnT-LLM to automate the process of end-to-end label generation and assignment for text mining using large language models, where LLMs produce and refine a label taxonomy iteratively using a zero-shot, multi-stage reasoning approach, and are used as data labelers to yield training samples for lightweight supervised classifiers. The framework is applied to the analysis of user intent and conversational domain for Bing Copilot, achieving accurate and relevant label taxonomies and a favorable balance between accuracy and efficiency for classification at scale.
- provides list of 55 categorical encoders, explains how to use the code as a supplement to Category Encoders Python module.
- categorizes encoders into families, explains how to reuse code from the benchmark to include your encoder or dataset in comparison
ColBERT is a new way of scoring passage relevance using a BERT language model that substantially solves the problems with dense passage retrieval.
A ready-to-run tutorial in Python and scikit-learn to evaluate a classification model compared to a baseline model
- Embeddings transform words and sentences into sequences of numbers for computers to understand language.
- This technology powers tools like Siri, Alexa, Google Translate, and generative AI systems like ChatGPT, Bard, and DALL-E.
- In the early days, embeddings were crafted by hand, which was time-consuming and couldn't adapt to language nuances easily.
- The 3D hand-crafted embedding app provides an interactive experience to understand this concept.
- The star visualization method offers an intuitive way to understand word embeddings.
- Machine learning models like Word2Vec and GloVe revolutionized the generation of word embeddings from large text datasets.
- Universal Sentence Encoder (USE) extends the concept of word embeddings to entire sentences.
- TensorFlow Projector is an advanced tool to interactively explore high-dimensional data like word and sentence embeddings.
Apply sound data-based anomalous behavior detection, diagnose the root cause via object detection concurrently, and inform the user via SMS.
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