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Lingua Franca — Entity-Aware Machine Translation Approach for Question Answering over Knowledge Graphs | by Aleksandr Perevalov | Jan, 2024

Towards a lingua franca for knowledge graph question answering systems Machine Translation (MT) can enhance existing Question Answering (QA) systems, which have limited language capabilities, by enabling them to support multiple languages. However, there is one major drawback of MT — often, it fails at translating named entities that are not translatable word-by-word. For example,…

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How to Use Zero-Shot Classification for Sentiment Analysis | by Aminata Kaba | Jan, 2024

Exploring mental well-being insights with zero-shot classification Artwork by Vivian Peng — reposted with permissionSentiment analysis is a powerful tool in natural language processing (NLP) for exploring public opinions and emotions in text. In the context of mental health, it can provide compelling insights into the holistic wellness of individuals. As a summer data science…

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Jump-start Your RAG Pipelines with Advanced Retrieval LlamaPacks and Benchmark with Lighthouz AI | by Wenqi Glantz | Jan, 2024

Exploring robust RAG development with LlamaPacks, Lighthouz AI, and Llama Guard Image generated by DALL-E 3 by the authorSince the launch in late November 2023, LlamaPacks has curated over 50 packs to help jump-start your RAG pipeline development. Among these, many advanced retrieval packs emerged. In this article, let’s dive into seven advanced retrieval packs;…

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Cypher Generation: The Good, The Bad and The Messy | by Silvia Onofrei | Jan, 2024

Methods for creating fine-tuning datasets for text-to-Cypher generation. Created with ChatGPT-DALLECypher is Neo4j’s graph query language. It was inspired and bears similarities with SQL, enabling data retrieval from knowledge graphs. Given the rise of generative AI and the widespread availability of large language models (LLMs), it is natural to ask which LLMs are capable of…

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How I’d Learn Machine Learning (If I Could Start Over) | by Egor Howell | Jan, 2024

Machine learning revolves around algorithms, which are essentially a series of mathematical operations. These algorithms can be implemented through various methods and in numerous programming languages, yet their underlying mathematical principles are the same. A frequent argument is that you don’t need to know maths for machine learning because most modern-day libraries and packages abstract…

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