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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning Blog

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. For more information, refer to Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data.

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23 Best Free NLP Datasets for Machine Learning

Iguazio

Twitter US Airline Sentiment Polarized Tweets from February 2015 about the large US airlines. 20 Newsgroups A dataset containing roughly 20,000 newsgroup documents spanning a variety of topics, for text classification, text clustering and similar ML applications. Get the dataset here. Get the dataset here. Synonyms 12.

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Building Meta’s GenAI Infrastructure

Hacker News

Marking a major investment in Meta’s AI future, we are announcing two 24k GPU clusters. We use this cluster design for Llama 3 training. We built these clusters on top of Grand Teton , OpenRack , and PyTorch and continue to push open innovation across the industry. The other cluster features an NVIDIA Quantum2 InfiniBand fabric.

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Best Machine Learning Frameworks for ML Experts in 2023

Pickl AI

It is not a good when dealing with RNN (Recurrent Neural Networks) Also See: 5 Machine Learning Algorithms That Every ML Engineer Should know Microsoft CNTK CNTK is a deep learning framework that was created by Microsoft Research. It is an open source framework that has been available since April 2015. It is very fast and supports GPU.

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Top 6 Kubernetes use cases

IBM Journey to AI blog

Nodes run the pods and are usually grouped in a Kubernetes cluster, abstracting the underlying physical hardware resources. In 2015, Google donated Kubernetes as a seed technology to the Cloud Native Computing Foundation (CNCF) (link resides outside ibm.com), the open-source, vendor-neutral hub of cloud-native computing.

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Robustness of a Markov Blanket Discovery Approach to Adversarial Attack in Image Segmentation: An…

Mlearning.ai

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., 2015; Huang et al., 2015), which consists of 20 object categories with varying levels of complexity. 2015) to generate adversarial examples for each image.

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Netflix Movies and Series Recommendation Systems

PyImageSearch

Figure 4: The Netflix personalized home page generation problem (source: Alvino and Basilico, “Learning a Personalized Homepage,” Netflix Technology Blog , 2015 ). Machine learning (ML) approaches can be used to learn utility functions by training it on historical data of which home pages have been created for members (i.e.,