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Search enterprise data assets using LLMs backed by knowledge graphs

Flipboard

In the context of enterprise data asset search powered by a metadata catalog hosted on services such Amazon DataZone, AWS Glue, and other third-party catalogs, knowledge graphs can help integrate this linked data and also enable a scalable search paradigm that integrates metadata that evolves over time.

Metadata 149
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Deploy pre-trained models on AWS Wavelength with 5G edge using Amazon SageMaker JumpStart

AWS Machine Learning Blog

As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers to reduce latency and increase responsiveness of their applications. Even ground and aerial robotics can use ML to unlock safer, more autonomous operations.

BERT 103
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A New Study from the University of Wisconsin Investigates How Small Transformers Trained from Random Initialization can Efficiently Learn Arithmetic Operations Using the Next Token Prediction Objective

Marktechpost

They can provide a logical justification for such phase changes thanks to this link. Data on the flow of cognition throughout training. Based on these findings, they investigate the possible advantages of chain-of-thought data during training. Check out the Paper and Github link. Training with text and math mixes.

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Predictive Maintenance using Azure Machine Learning AutoML and Inference using Managed Online…

Mlearning.ai

with sdk v2 import libraries import tqdm import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sns sns.set_style("whitegrid") import the data set # Import required libraries from azure.identity import DefaultAzureCredential from azure.identity import AzureCliCredential from azure.ai.ml

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Present and future of data cubes: an European EO perspective

Mlearning.ai

Most important to note about ARCO is that, unlike data systems from a decade ago, modern data cubes should ideally be Cloud-native (meaning: ready for fast and efficient web-services / scalable applications / API’s) and pre-processed so that they can be directly used for modelling and eventually for decision-making.

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Supercharging Your Data Pipeline with Apache Airflow (Part 2)

Heartbeat

If you have an idea about both but don't have docker or docker-compose installed on your system, you can check out this link for installing both on Ubuntu. Windows and Mac have docker and docker-compose packaged into one application, so if you download docker on Windows or Mac, you have both docker and docker-compose.

ETL 52
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Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit?—?Part 2 of 3

Mlearning.ai

In this article, we will cover the third & fourth sections i.e. Data Extraction, Preprocessing & EDA & Machine Learning Model development Data collection : Automatically download the stock historical prices data in CSV format and save it to the AWS S3 bucket. Please refer to this documentation link.

Python 52