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Harness the Power of Pinecone with Cloudera’s New Applied Machine Learning Prototype

Cloudera

And so we are thrilled to introduce our latest applied ML prototype (AMP) — a large language model (LLM) chatbot customized with website data using Meta’s Llama2 LLM and Pinecone’s vector database. We invite you to explore the improved functionalities of this latest AMP.

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Of Muffins and Machine Learning Models

Cloudera

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. In this article, we explore model governance, a function of ML Operations (MLOps). Machine Learning Model Lineage. Machine Learning Model Visibility .

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning - AI

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. We then discuss how building on a secure foundation is essential for generative AI.

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The impact of AI on edge computing

CIO

AI, including Generative AI (GenAI), has emerged as a transformative technology, revolutionizing how machines learn, create, and adapt. Read more about the impacts AI at the edge is predicted to have on the manufacturing industry in this recent blog. billion in 2027 with a compound annual growth rate (CAGR) of 86.1%

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Therefore, the majority of machine learning/deep learning frameworks focus on Python APIs.

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Understanding Data Storage: Lakes vs. Warehouses

DevOps.com

They are frequently turning to complex data for tasks like machine learning and artificial intelligence, which are becoming necessary to understand and reach customer segments across industries. The post Understanding Data Storage: Lakes vs. Warehouses appeared first on DevOps.com.

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Building a Machine Learning Application With Cloudera Data Science Workbench And Operational Database, Part 1: The Set-Up & Basics

Cloudera

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle. Example Operations .