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Traditional vs Vector databases: Your guide to make the right choice

Data Science Dojo

Here’s your guide to top vector databases in the market Query language Traditional databases: They rely on Structured Query Language (SQL), designed to navigate through relational databases. SQL querying has long been present in the industry, hence it comes with a rich ecosystem of support.

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KDnuggets™ News 19:n38, Oct 9: The Last SQL Guide for Data Analysis; 4 Quadrants of Data Science Skills and 7 steps for Viral Data Visualization

KDnuggets

Read a comprehensive SQL guide for data analysis; Learn how to choose the right clustering algorithm for your data; Find out how to create a viral DataViz using the data from Data Science Skills poll; Enroll in any of 10 Free Top Notch Natural Language Processing Courses; and more.

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Was ist eine Vektor-Datenbank? Und warum spielt sie für AI eine so große Rolle?

Data Science Blog

Neben den relationalen Datenbanken (SQL) gibt es auch die NoSQL -Datenbanken wie den Key-Value-Store, Dokumenten- und Graph-Datenbanken mit recht speziellen Anwendungsgebieten. der k-Nächste-Nachbarn -Prädiktionsalgorithmus (Regression/Klassifikation) oder K-Means-Clustering.

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Explore data with ease: Use SQL and Text-to-SQL in Amazon SageMaker Studio JupyterLab notebooks

AWS Machine Learning Blog

In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them. They then use SQL to explore, analyze, visualize, and integrate data from various sources before using it in their ML training and inference.

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Monitoring of Jobskills with Data Engineering & AI

Data Science Blog

The data is obtained from the Internet via APIs and web scraping, and the job titles and the skills listed in them are identified and extracted from them using Natural Language Processing (NLP) or more specific from Named-Entity Recognition (NER). Why we did it? It is a nice show-case many people are interested in.

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Best practices for prompt engineering with Meta Llama 3 for Text-to-SQL use cases

AWS Machine Learning Blog

In this post, we provide an overview of the Meta Llama 3 models available on AWS at the time of writing, and share best practices on developing Text-to-SQL use cases using Meta Llama 3 models. Training involved a dataset of over 15 trillion tokens across two GPU clusters, significantly more than Meta Llama 2.

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Cracking the large language models code: Exploring top 20 technical terms in the LLM vicinity

Data Science Dojo

Transformers are a type of neural network that are well-suited for natural language processing tasks. They are able to learn long-range dependencies between words, which is essential for understanding the nuances of human language. They are typically trained on clusters of computers or even on cloud computing platforms.