Search

Refine your search
  • [x] Creation time: Last year
Sort order
Content type
Keywords
100%
Automating deployments on Proxmox with OpenTofu and cloud-init
04.12.2024
Home »   » 
Lead Image © lightwise, 123RF.com
Rubén Llorente ... ). Listing 3 tofu_project/main.tf 01 terraform { 02 required_providers { 03 proxmox = { 04 source = "bpg/proxmox" 05 version = "0.64.0" 06 } 07 } 08 } 09 10 provider "proxmox
16%
Code IaC for provisioning of preconfigured virtual environments
26.01.2025
Home »   »   »   » 
Lead Image © vladnikon, 123RF.com
Name .. .. } 03 04 resource devcenterGallery 'Microsoft.DevCenter/devcenters/galleries@2024-02-01' = { 05 name: galleryName 06 parent: devcenter 07 ... 08 dependsOn: [ 09 readGalleryRole 10
16%
Introducing the NoSQL MongoDB database
04.12.2024
Home »   »   »   » 
Photo by Wesley Tingey on Unsplash
, 06 "mileage": 15000, 07 "features": ["Sunroof", "Leather seats"] 08 } 09 { 10 "type": "Motorcycle, 11 "brand: "Harley-Davidson, 12 "model": "Iron 883", 13 "year": 2019, 14 "engine
16%
Keras: Getting Started with AI
03.12.2024
Home »   »   » 
, MaxPooling 2D : model.add(layers.BatchNormalization()) model.add(layers.MaxPooling2D(pool_size=(2,2))) A max pooling layer has a pool size, 2x2 in this case, that is used to scan the entire input image (left
16%
Getting started with AI
26.01.2025
Home »   »   »   » 
Lead Image © Lightwise, 123RF.com
this second 2D convolution layer, you have another batch normalization layer followed by a new layer type, MaxPooling2D: model.add(layers.BatchNormalization()) model.add(layers.MaxPooling2D(pool_size=(2,2
16%
How vector databases work and when they're used
04.12.2024
Home »   »   »   » 
Lead Image © neyro2008, 123rf.com
={"city": "New York"}), PointStruct(id=5, vector=[0.24, 0.18, 0.22, 0.44], payload={"city": "Beijing"}), PointStruct(id=6, vector=[0.35, 0.08, 0.11, 0.44], payload={"city": "Mumbai"}),], ) The database
16%
Web applications with Julia
26.01.2025
Home »   »   »   » 
Lead Image © sony sivanandan, 123RF.com
startserver() 05 WebSockets.listen("127.0.0.1", PORT) do ws 06 for msg in ws 07 d = Meta.parse(JSON.parse(msg)["s"]) 08 WebSockets.send(ws, """

You picked $d