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Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

Flipboard

Recent advances in generative AI have led to the rapid evolution of natural language to SQL (NL2SQL) technology, which uses pre-trained large language models (LLMs) and natural language to generate database queries in the moment.

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5 Reasons Why SQL is Still the Most Accessible Language for New Data Scientists

ODSC - Open Data Science

For budding data scientists and data analysts, there are mountains of information about why you should learn R over Python and the other way around. Though both are great to learn, what gets left out of the conversation is a simple yet powerful programming language that everyone in the data science world can agree on, SQL.

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Automate invoice processing with Streamlit and Amazon Bedrock

AWS Machine Learning Blog

Streamlit is an open source framework for data scientists to efficiently create interactive web-based data applications in pure Python. In this post, we save the data in JSON format, but you can also choose to store it in your preferred SQL or NoSQL database. Install Python 3.7 or later on your local machine.

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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning Blog

To overcome these limitations, we propose a solution that combines RAG with metadata and entity extraction, SQL querying, and LLM agents, as described in the following sections. Typically, these analytical operations are done on structured data, using tools such as pandas or SQL engines.

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An integrated experience for all your data and AI with Amazon SageMaker Unified Studio (preview)

Flipboard

Data processing and SQL analytics Analyze, prepare, and integrate data for analytics and AI using Amazon Athena, Amazon EMR, AWS Glue, and Amazon Redshift. With SageMaker Unified Studio notebooks, you can use Python or Spark to interactively explore and visualize data, prepare data for analytics and ML, and train ML models.

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MongoRAG: Leveraging MongoDB Atlas as a Vector Database with Databricks-Deployed Embedding Model and LLMs for Retrieval-Augmented Generation

Towards AI

Now, as MongoDB is a NoSQL Database, we have to create a Database first (unlike Schema for SQL Databases, although the concept is same), then inside the Database we have to create a collection, in which we can store documents (It is like creating a table inside a Database). 70B Instruct models for this demo.

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Snowflake Snowpark: cloud SQL and Python ML pipelines

Snorkel AI

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

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