Google Kubernetes Engine Reviews

Scikit-learn Reviews

Google Kubernetes Engine mentions (45)

• 26 Top Kubernetes Tools

  Google Kubernetes Engine (GKE) is another managed Kubernetes service that lets you spin up new cloud clusters on demand. It's specifically designed to help you run Kubernetes workloads without specialist Kubernetes expertise, and it includes a range of optional features that provide more automation for admin tasks. These include powerful capabilities around governance, compliance, security, and configuration... - Source: dev.to / 3 days ago

• Kubernetes: Hello World

  Cloud Clusters: If you'd rather work in a cloud environment, consider platforms like Google Kubernetes Engine (GKE) or Amazon EKS for managed Kubernetes clusters. - Source: dev.to / 6 days ago

• Using Cloud Monitoring to Monitor IRIS-Based Applications Deployed in GKE

  In this article, we’ll look at one of the ways to monitor the InterSystems IRIS data platform (IRIS) deployed in the Google Kubernetes Engine (GKE). The GKE integrates easily with Cloud Monitoring, simplifying our task. As a bonus, the article shows how to display metrics from Cloud Monitoring in Grafana. - Source: dev.to / 22 days ago

• Using NetBird for Kubernetes Access

  Set up a remote Kubernetes cluster. For this tutorial, Google Kubernetes Engine (GKE) was chosen; however, feel free to use any remote Kubernetes cluster. - Source: dev.to / about 2 months ago

• The 2024 Web Hosting Report

  Docker swarm still exists, it still works, and some of these other container orchestrators are still hanging on, but for the most part, you’re using Kubernetes if you’re doing this stuff at work. Generally it's well-understood that kubernetes is hard to get right, and so most people use it via a managed provider like Elastic Kubernetes Service from AWS, Azure Kubernetes Service from MSFT, or Google Kubernetes... - Source: dev.to / 4 months ago

Scikit-learn mentions (28)

• How to Build a Logistic Regression Model: A Spam-filter Tutorial

  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 / 3 months ago

• Link Prediction With node2vec in Physics Collaboration Network

  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 / 12 months ago

• WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point

  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: about 1 year ago

• PSA: You don't need fancy stuff to do good work.

  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: about 1 year ago

• Help on using R for Machine Learning?

  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: over 1 year ago