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Acoustic Model Fusion for End-to-end Speech Recognition

Machine Learning Research at Apple

Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted its accuracy to a new level. Despite this simpler system architecture, fusing a separate LM, trained exclusively on text corpora, into the E2E system has proven to be beneficial.

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Rad AI reduces real-time inference latency by 50% using Amazon SageMaker

AWS Machine Learning Blog

Challenges in deploying advanced ML models in healthcare Rad AI, being an AI-first company, integrates machine learning (ML) models across various functions—from product development to customer success, from novel research to internal applications. Let’s transition to exploring solutions and architectural strategies.

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9 Careers You Could Go into With a Data Science Degree

Smart Data Collective

Machine Learning Engineer. As a machine learning engineer, you would create data funnels and deliver software solutions. As well as designing and building machine learning systems, you could be responsible for running tests and monitoring the functionality and performance of systems.

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Build a dynamic, role-based AI agent using Amazon Bedrock inline agents

AWS Machine Learning Blog

To understand how this dynamic role-based functionality works under the hood, lets examine the following system architecture diagram. As shown in preceding architecture diagram, the system works as follows: The end-user logs in and is identified as either a manager or an employee.

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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. He works with customers from different sectors to accelerate high-impact data, analytics, and machine learning initiatives.

ML 93
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Embedded AI Integration with MATLAB and Simulink

Pickl AI

Simulink provides blocks specifically designed for AI functions, allowing you to incorporate Machine Learning or deep learning models seamlessly. Training : Train your model using MATLAB’s built-in functions or toolboxes like the Deep Learning Toolbox. Model Selection : Choose appropriate algorithms (e.g.,

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A Guide to LLMOps: Large Language Model Operations

Heartbeat

This is brought on by various developments, such as the availability of data, the creation of more potent computer resources, and the development of machine learning algorithms. Deployment : The adapted LLM is integrated into this stage's planned application or system architecture.