AWS Machine Learning Blog

NOVEMBER 16, 2023

Photo by Scott Webb on Unsplash Determining the value of housing is a classic example of using machine learning (ML). Almost 50 years later, the estimation of housing prices has become an important teaching tool for students and professionals interested in using data and ML in business decision-making.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

We start with an introduction of the Cost Optimization pillar and design principles, and then dive deep into the four focus areas: financial management, resource provision, data management, and cost monitoring. If you’re not actively using the endpoint for an extended period, you should set up an auto scaling policy to reduce your costs.

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Heartbeat

DECEMBER 27, 2023

In computing, virtualization creates a virtual copy of a physical IT infrastructure and resources such as hardware, application storage, network, desktop/Operating system (OS), data, CPU/GPU, and simulates functionality. Docker APIs interact with the Docker daemon through the CLI commands or scripting. Prerequisite Python 3.8

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Chatbots Life

MAY 19, 2023

People rely on conversational AI and virtual assistants to do anything from purchasing a trip to scheduling a doctor’s appointment in the present digital environment. A chatbot is a technological genie that uses intelligent automation, ML, and NLP to automate tasks. Your staff can auto-resolve issues using this ticketing system.

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

You can easily try out these models and use them with SageMaker JumpStart, which is a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. In this post, we walk through how to fine-tune Llama 2 pre-trained text generation models via SageMaker JumpStart.

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The MLOps Blog

MARCH 23, 2023

Even if you are fine-tuning an average-sized model for a large-scale application, you need to muster a huge amount of data. In Distributed inference, LLM is deployed on multiple machines, with each machine processing a subset of the input data. To understand more on this subject you can read the blog here. 2020 or Hoffman et al.,

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AWS Machine Learning Blog

MAY 30, 2023

Since its introduction, we have helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage. Notebooks contain everything needed to run or recreate an ML workflow. You can build custom queries to look up AWS CUR data using standard SQL.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing. The potential exists to fine-tune VLMs and LLMs further using domain-specific data, aiming to boost precision and mitigate hallucination.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate machine learning (ML) predictions for their business needs. Optimized for handling categorical variables. This flexibility can provide more robust and insightful model development.

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