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Azure Kubernetes Service (AKS) Azure Kubernetes Service (AKS) is a managed Kubernetes offering from Microsoft Azure. It enables users to deploy and manage containerized applications using Kubernetes without the need to manage the underlying infrastructure. AKS integrates with Azure services like Azure Container Registry, Azure Monitor, and Azure Active Directory, providing a comprehensive solution for deploying... - Source: dev.to / 3 months ago
Container Orchestration tools: These are used to automate the deployment, scaling, monitoring, and management of containerized applications. These tools simplify the complexities of managing and coordinating containers across a cluster of machines. They include Kubernetes, Docker Swarm, Amazon ECS, Microsoft AKS, Google Kubernetes Engine (GKE), etc. - Source: dev.to / 4 months ago
When you want the "full" Nuxt experience, you will need to host the Node.js process. This can be done with Azure app service, Azure container instances, Azure container apps or even AKS. Source: 11 months ago
Microsoft recently announced the general availability release of AKS Edge Essentials, a new Azure Kubernetes Service (AKS) offering designed to simplify edge computing for developers and IT professionals. See InfoQ News item: https://www.infoq.com/news/2023/03/aks-edge-essentials-ga/. Source: about 1 year ago
UNIX is irrelevant on the cloud, unless one is stuck deploying legacy workloads on VMs, this is what we use in modern applications not stuck in the past. https://aws.amazon.com/eks/ https://azure.microsoft.com/en-us/products/kubernetes-service https://cloud.google.com/kubernetes-engine/ https://cloud.google.com/appengine https://azure.microsoft.com/en-us/products/app-service https://aws.amazon.com/lambda/... - Source: Hacker News / about 1 year ago
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
Google Kubernetes Engine - Google Kubernetes Engine is a powerful cluster manager and orchestration system for running your Docker containers. Set up a cluster in minutes.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Apache Karaf - Apache Karaf is a lightweight, modern and polymorphic container powered by OSGi.
OpenCV - OpenCV is the world's biggest computer vision library
Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.
NumPy - NumPy is the fundamental package for scientific computing with Python