Machine Learning | News, how-tos, features, reviews, and videos
Amazon Bedrock smooths the path to building generative AI apps with prompt engineering and RAG, providing a good assortment of text, chat, and image-based foundation models.
Five key questions you should ask before embarking on the journey to create your own in-house large language model.
LinkedIn needed a better way to test and tune machine learning models, so it wrote its own tool that plugs into Visual Studio Code.
Microsoft Fabric is an end-to-end suite of cloud-based tools for data analytics, encompassing data movement, data storage, data engineering, data integration, data science, real-time analytics, and business intelligence.
Learn how to build and deploy a machine-learning data model in a Java-based production environment using Weka, Docker, and REST.
Set up a supervised learning project, then develop and train your first prediction function using gradient descent in Java.
Great documentation is important for humans, but more so for machines. The concept of ‘tiered documentation’ means that both developers and LLMs get what they need.
The JFrog Amazon SageMaker integration incorporates machine learning models into the software development lifecycle.
Ever-larger datasets for AI training pose big challenges for data engineers and big risks for the models themselves.
Rate limits mean everyone is waiting for better compute resources or different generative AI models.