AWS Machine Learning Blog

APRIL 4, 2023

AWS provides various services catered to time series data that are low code/no code, which both machine learning (ML) and non-ML practitioners can use for building ML solutions. Solution overview Clustering is an unsupervised ML technique that groups items together based on a distance metric. to avoid overfitting.

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AWS Machine Learning Blog

AUGUST 21, 2023

Advances in NLP models, such as Bi-directional Encoder Representations from Transformers (BERT), have allowed for highly accurate predictions on a corpus of text, such as admission notes, that were previously difficult to get value from. What is SHAP SHAP values are a technique for explaining the output of ML models.

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AWS Machine Learning Blog

FEBRUARY 20, 2024

The engagement focused on delivering a functional solution for the localization process, while providing hands-on training to ZOO Digital developers on SageMaker, Amazon Transcribe , and Amazon Translate. Solution overview In this prototype, we stored the original media files in a specified Amazon Simple Storage Service (Amazon S3) bucket.

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AWS Machine Learning Blog

FEBRUARY 9, 2024

We describe how the solution and Amazon Bedrock consumption plans map to the general SaaS journey framework. The code for the solution and an AWS Cloud Development Kit (AWS CDK) template is available in the GitHub repository. For simplicity, we do not include these in this solution. model_id – The ID of the model to be invoked.

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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. max_train_samples – For debugging purposes or quicker training, truncate the number of training examples to this value.

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Heartbeat

DECEMBER 13, 2023

You can define tools that perform complex calculations, interact with external APIs, manipulate data uniquely, or integrate with other systems. In that case, you can define custom financial calculations or data analysis tools tailored to your needs. Integration: Custom tools can integrate LangChain with other systems or tools.

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Explosion

OCTOBER 18, 2016

now makes it much easier to calculate those annotations using your own custom models. The embeddings table is large, and the values provided by the pre-trained vectors are already pretty good. However, the concerns of these libraries usually end at the point where you have an evaluation score and a model file.

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