AWS Machine Learning Blog

JUNE 15, 2023

Rachel Hu is an applied scientist at AWS Machine Learning University (MLU). Before joining AWS, Rachel worked as a machine learning engineer building natural language processing models. Before joining AWS, Rachel worked as a machine learning engineer building natural language processing models.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

With the introduction of EMR Serverless support for Apache Livy endpoints , SageMaker Studio users can now seamlessly integrate their Jupyter notebooks running sparkmagic kernels with the powerful data processing capabilities of EMR Serverless. elasticmapreduce", "arn:aws:s3:::*.elasticmapreduce/*" elasticmapreduce", "arn:aws:s3:::*.elasticmapreduce/*"

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Dataconomy

OCTOBER 22, 2024

When AlexNet, a CNN-based model, won the ImageNet competition in 2012, it sparked widespread adoption in the industry. “For example, companies have released massive datasets, such as those for image recognition, language models, and self-driving car simulations, that have become critical for academic research. .

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AWS Machine Learning Blog

MAY 12, 2023

Amazon SageMaker comes with two options to spin up fully managed notebooks for exploring data and building machine learning (ML) models. The first option is fast start, collaborative notebooks accessible within Amazon SageMaker Studio —a fully integrated development environment (IDE) for machine learning.

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Dataconomy

AUGUST 10, 2023

With the application of natural language processing (NLP) and machine learning algorithms, AI systems can understand and translate spoken language into written notes. It can also help with retrieving information from electronic health records (EHRs) and other tasks to alleviate administrative burdens.

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AWS Machine Learning Blog

OCTOBER 1, 2024

We demonstrate the process of integrating Anthropic Claude’s advanced natural language processing capabilities with the serverless architecture of Amazon Bedrock, enabling the deployment of a highly scalable and cost-effective solution. For our LLM, we use Anthropic Claude on Amazon Bedrock.

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Dataconomy

JUNE 15, 2023

Another significant milestone came in 2012 when Google X’s AI successfully identified cats in videos using over 16,000 processors. This demonstrated the astounding potential of machines to learn and differentiate between various objects. The challenge with big data lies in its volume, velocity, and variety.

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AWS Machine Learning Blog

APRIL 5, 2023

Amazon Rekognition makes it easy to add this capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

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IBM Journey to AI blog

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. IBM watsonx.ai Explore watsonx.ai

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Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube YouTube Introduction to Natural Language Processing (NLP) NLP 2012 Dan Jurafsky and Chris Manning (1.1)

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AWS Machine Learning Blog

MARCH 12, 2024

t “enclave_base” Save the LLM in the EC2 Instance We are using the open-source Bloom 560m LLM for natural language processing to generate responses. Their research focuses on privacy-preserving machine learning. This model is not fine-tuned to PII and PHI, but demonstrates how an LLM can live inside of an enclave.

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Applied Data Science

MARCH 11, 2022

Back in 2012 things were quite different. How can you tell which features are the most appropriate, before giving them to a machine learning model? Language as a game: the field of Emergent Communication Firstly, what is language? This cat does not exist. All the rage was about algorithms for classification.

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Pickl AI

JULY 24, 2024

Key milestones include the Turing Test, the Dartmouth Conference, and breakthroughs in machine learning. ” During this time, researchers made remarkable strides in natural language processing, robotics, and expert systems. In 2011, IBM’s Watson gained fame by winning the quiz show “Jeopardy!

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AWS Machine Learning Blog

APRIL 16, 2024

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them. or later image versions.

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Towards AI

JULY 21, 2023

Photo by Will Truettner on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 07.26.20 Last Updated on July 21, 2023 by Editorial Team Author(s): Ricky Costa Originally published on Towards AI. Primus The Liber Primus is unsolved to this day.

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AWS Machine Learning Blog

JULY 10, 2024

Solution overview Fine-tuning is a technique in natural language processing (NLP) where a pre-trained language model is customized for a specific task. Fang Liu is a principal machine learning engineer at Amazon Web Services, where he has extensive experience in building AI/ML products using cutting-edge technologies.

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AWS Machine Learning Blog

DECEMBER 14, 2023

Amazon SageMaker Studio offers a broad set of fully managed integrated development environments (IDEs) for machine learning (ML) development, including JupyterLab, Code Editor based on Code-OSS (Visual Studio Code Open Source), and RStudio. About the authors Pranav Murthy is an AI/ML Specialist Solutions Architect at AWS.

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Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., 2012; Otsu, 1979; Long et al., an image) with the intention of causing a machine learning model to misclassify it (Goodfellow et al.,

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Heartbeat

AUGUST 21, 2023

AlexNet is a more profound and complex CNN architecture developed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton in 2012. Natural Language Processing : CNNs have been implemented for sentiment analysis and text categorization in natural language processing jobs.

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AWS Machine Learning Blog

JUNE 6, 2023

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural language processing, content creation, and more. Kanwaljit specializes in helping customers with containerized and machine learning applications.

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Explosion

DECEMBER 28, 2019

Jan 28: Ines then joined the great lineup of Applied Machine Learning Days in Lausanne, Switzerland. Sofie has been involved with machine learning and NLP as an engineer for 12 years. Adriane is a computational linguist who has been engaged in research since 2005, completing her PhD in 2012.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). in 2012 is now widely referred to as ML’s “Cambrian Explosion.” Machine learning Generative AI is the most topical ML application at this point in time. Work by Hinton et al.

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Snorkel AI

APRIL 25, 2023

With that said, I’m actually a faculty member at Harvard, and one of my key goals is to help—both academically as well as from an industry perspective—work with MLCommons , which is a nonprofit organization focusing on accelerating benchmarks, datasets, and best practices for ML (machine learning).

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Snorkel AI

APRIL 25, 2023

With that said, I’m actually a faculty member at Harvard, and one of my key goals is to help—both academically as well as from an industry perspective—work with MLCommons , which is a nonprofit organization focusing on accelerating benchmarks, datasets, and best practices for ML (machine learning).

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Explosion

FEBRUARY 18, 2015

spaCy is a new library for text processing in Python and Cython. I wrote it because I think small companies are terrible at natural language processing (NLP). To do great NLP, you have to know a little about linguistics, a lot about machine learning, and almost everything about the latest research.

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AWS Machine Learning Blog

APRIL 23, 2024

We are excited to announce two new capabilities in Amazon SageMaker Studio that will accelerate iterative development for machine learning (ML) practitioners: Local Mode and Docker support. Tips for using SageMaker Local Mode If you’re using SageMaker for the first time, refer to Train machine learning models.

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Data Science Blog

SEPTEMBER 3, 2024

Process Mining Tools, die als pure Process Mining Software gestartet sind Hierzu gehört Celonis, das drei-köpfige und sehr geschäftstüchtige Gründer-Team, das ich im Jahr 2012 persönlich kennenlernen durfte. Aber Celonis war nicht das erste Process Mining Unternehmen. Es gab noch einige mehr. Hier fällt mir z.

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DrivenData Labs

MAY 1, 2025

His research focuses on applications of Network Analysis and Natural Language Processing, and he has extensive experience working with real-world data across diverse domains. changes between 2003 and 2012). Artem Volgin recently completed a PhD in Social Statistics at the University of Manchester, UK.

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AWS Machine Learning Blog

JULY 15, 2025

He has delivered end-to-end machine learning systems backed by solid MLOps practices—enabling scalable model training, real-time inference, continuous evaluation, and robust monitoring in production environments. Replace YOUR_ACCOUNT_ID with your AWS account number. Leave PLACEHOLDER_IDENTITY_POOL_ID as is for now.

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AWS Machine Learning Blog

OCTOBER 11, 2024

For example: Data such as images, text, and audio need to be represented in a structured and efficient manner Understanding the semantic similarity between data points is essential in generative AI tasks like natural language processing (NLP), image recognition, and recommendation systems As the volume of data continues to grow rapidly, scalability (..)

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