as well as the ability to easily migrate and share between private and public clouds. The popularity of Amazon EKS (12%) and Docker Swarm (12%) might be attributable to the balance they offer between manageability and scalability, catering to various deployment needs. ...
I’ll discuss the various migration libraries that exist to help convert Python 2.x applications to Python 3.x. Using code samples that leverage three methods for Python migration (2to3, python-future, six), I’ll show how you can get started quickly on application ...
PhysicsNeMo Makani: Experimental library designed to enable the research and development of machine-learning based weather and climate models. Earth2 Grid: Experimental library with utilities for working geographic data defined on various grids.
Spark NLP provides a range of models to tackle various NLP tasks. These models are often pre-trained on large datasets and can be fine-tuned or used directly for inference. Some of the primary categories and examples of Spark NLP models include: 1. Named Entity Recognition (NER): Pre-train...
Spark NLP provides easy support for importing models from various popular frameworks: TensorFlow ONNX OpenVINO Llama.cpp (GGUF) This wide range of support allows you to seamlessly integrate models from different sources into your Spark NLP workflows, enhancing flexibility and compatibility with existing...
This quick read introduces the various ways that Python code has been made available for use, as well as how to work with them. No matter which type of package you prefer to work with, you should always build Python packages from source to ensure against compromised binaries. The Active...
69. GNN models have been found to achieve SOTA performance for various materials property prediction tasks. CGCNN60, MEGNet63, GATGNN68, SchNet69, and MPNN70are some of the well-known GNN models for materials property prediction that use graph representation learning. One of the problems of ...
Solid-state Li–S batteries (SSLSBs) are made of low-cost and abundant materials free of supply chain concerns. Owing to their high theoretical energy densities, they are highly desirable for electric vehicles1–3. However, the development of SSLSBs has
The energy ecosystem data space forms the foundation of the energy metaverse. This data space should securely store and share data from multiple sources and of various types within the energy metaverse. It should also facilitate secure data exchange with third-party systems via Application Programming...
(covid-blood-severity). The application of DISCERN to the covid-blood dataset (COVID-19 patient blood) enabled us to detect 24 different immune cell types and activity states, which is quite remarkable given that we find these cells in blood. Two TH17 subtypes caught our attention, as ...