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 RIP(Routing Information Protocol) Being one of the Oldest distance vector routing protocols, RIP is based on the Bellman-ford algorithm.  There are two versions of this protocol, which were published in 1998. We can find the complete documentation on internetsociety.org the file is located at  RIP Official Documentation . GNS3 Many professionals and students use Graphical Network Simulator to experiment with networking paradigms. we are using it to emulate the RIP routing algorithm. Components VPCs - 2 switch - 2 router(c7200) - 3 Topology Topology constructed for this exercise   Commands to set the IP address to interfaces in the router config interface <Interface_Name> ip address <IP_addr> <Mask> no shutdown Commands used for initiating the RIP routing in a server are as follows config router rip network <subnet1_network_addr> network <subnet2_network_addr> if all the commands are entered correctly we will see a result similar to...

AWS CodeBuild is a service provided by AWS for all the project build requirements. it is a module which will be part of AWS CodePipeline service.  This below instructions are aimed for beginners and advance configurations are not covered, users are encouraged to explore while understanding the basics. be aware that for each build you will be billed for the resource you use please check the billing calculator. Step 1: Search for CodeBuild service in AWS web console and click on it. Step 2: select "create build project" for creating new build configuration here you can enter the name for your project and also select the platform which contains your source code you want to build. available options are shown below. sample GitHub connection look something like below picture. Step 3: now we have to setup our environment to be used for our build here we can either choose a AWS managed Docker images or our own images for the build. There are different version of images to select from...

K-means classification K-means, a simple Machine learning algorithm used for classification purposes. Machine learning is an awesome field, full of interesting topics and scenarios to study. While starting in this track one of the basics we study is classifiers, these things can be complex as hell and also easy as watching Tom chasing Jerry on television. I have implemented the K-means with a simple NumPy library of python 3. It’s a good start for someone who is started to learn or teaching this classifier. No Oop used, just some function call which intern makes some more function calls. View the full code in my GitHub repository follow this link K-means notebook