AWS Machine Learning Blog

Category: Amazon ML Solutions Lab

Deploy trained Keras or TensorFlow models using Amazon SageMaker

This post was reviewed and updated May 2022, to enforce model results reproducibility, add reproducibility checks, and to add a batch transform example for model predictions. Previously, this post was updated March 2021 to include SageMaker Neo compilation. Updated the compatibility for model trained using Keras 2.2.x with h5py 2.10.0 and TensorFlow 1.15.3. Amazon SageMaker […]

Create a Word-Pronunciation sequence-to-sequence model using Amazon SageMaker

Amazon SageMaker seq2seq offers you a very simple way to make use of the state-of-the-art encoder-decoder architecture (including the attention mechanism) for your sequence to sequence tasks. You just need to prepare your sequence data in recordio-protobuf format and your vocabulary mapping files in JSON format. Then you need to upload them to Amazon Simple […]

Introducing the Amazon ML Solutions Lab

We are excited to announce the Amazon ML Solutions Lab, a new program that connects machine learning experts from across Amazon with AWS customers to help identify novel uses of machine learning inside customers’ businesses, and guide them in developing new machine learning-enabled features, products, and processes. Amazon has been investing in machine learning for more than 20 years, innovating in areas such as fulfilment and logistics, personalization and recommendations, forecasting, fraud prevention, and supply chain optimization. The Amazon ML Solutions Lab provides you access to the same talent that built many of Amazon’s machine learning-powered products and services.