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Top NLP Skills, Frameworks, Platforms, and Languages for 2023

ODSC - Open Data Science

Developing NLP tools isn’t so straightforward, and requires a lot of background knowledge in machine & deep learning, among others. Machine & Deep Learning Machine learning is the fundamental data science skillset, and deep learning is the foundation for NLP.

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Get started quickly with AWS Trainium and AWS Inferentia using AWS Neuron DLAMI and AWS Neuron DLC

AWS Machine Learning Blog

Starting with the AWS Neuron 2.18 release , you can now launch Neuron DLAMIs (AWS Deep Learning AMIs) and Neuron DLCs (AWS Deep Learning Containers) with the latest released Neuron packages on the same day as the Neuron SDK release. AWS Systems Manager Parameter Store support Neuron 2.18

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Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker

AWS Machine Learning Blog

Llama2 by Meta is an example of an LLM offered by AWS. To learn more about Llama 2 on AWS, refer to Llama 2 foundation models from Meta are now available in Amazon SageMaker JumpStart. Virginia) and US West (Oregon) AWS Regions, and most recently announced general availability in the US East (Ohio) Region.

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Model Development Data Scientists develop sophisticated machine-learning models to derive valuable insights and predictions from the data. These models may include regression, classification, clustering, and more. Machine Learning: Supervised and unsupervised learning techniques, deep learning, etc.

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Creating an artificial intelligence 101

Dataconomy

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. Develop AI models using machine learning or deep learning algorithms. Machine learning and deep learning algorithms are commonly used in AI development.

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Accelerate PyTorch with DeepSpeed to train large language models with Intel Habana Gaudi-based DL1 EC2 instances

AWS Machine Learning Blog

Libraries such as DeepSpeed (an open-source deep learning optimization library for PyTorch) address some of these challenges, and can help accelerate model development and training. Training setup We provisioned a managed compute cluster comprised of 16 dl1.24xlarge instances using AWS Batch. Pre-training of a 1.5-billion-parameter

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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Prerequisites To continue with the examples in this post, you need to create the required AWS resources.

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