This blog summarizes what I have learned about HTTP and RESTful API during Winter of Doing program.

The blog shares my experience in the CWOD program and explains everything I have learned in Stage1.

Crio.Do is trying its best to fill the gap between the skill set of pursuing engineering students and the skillset required in the industry. This is a great initiative to train the students to understand the work environment and employees to upgrade their competency.


In today’s fast-paced world, automation provides us with the speed and accuracy we need. The greater all industries' access to Automation, the greater our lives become on the whole.

This project is about creating an automatic setup for an organization.

In this project, three aspects are considered which includes

  • how a developing team works on a central version controlling system
  • how a webpage is tested by the Quality Assurance Team, and then
  • how a webpage is deployed finally for the clients.


I would like to express my sincere gratitude to Vimal Daga Sir, who has guided me in this project.


The article explains how to launch a website, on the Kubernetes cluster using GKE and Load Balancer services provided by Google Cloud Platform.


Kubernetes is one tool that helps in container orchestration. Google provides a superb way to manage Kubernetes services, through GKE (Google Kubernetes Engine). Kubernetes deployments help us in launching and saving the information in case of accidental deletion.

Working in a Kubernetes cluster increases the flexibility of resource usage. Now the available resources are not limited to resources of one node only. The master node will decide in which slave node a pod will be launched.

Both SQL Server and Kubernetes Cluster will be launched in different private networks and will be linked using VPC peering.

Cloud computing allows us to use resources active across the continent. There are many cases in which the connection between Private Networks launched in the different regions needs to be connected.

In this blog, I have explained how does the google Kubernetes engine work. This article will explain the connectivity of two VPC Network launched in a different region.


  • Create multiple projects and one VPC in each of them.
  • Establish a link between both the VPC networks using VPC Peering.
  • Create a Kubernetes Cluster in one project and launch any web application with the load balancer.
  • Create a SQL server

The blog contains a brief on concepts of various services in GCP and detailed procedure of launching an Instance and VPC peering.

Why we need Cloud Services!!?

To run any program, we need an Operating System. And the operating system is also a collection of programs, a software that runs on the hardware. To run any program be it of DBMS servers, ML programs, web hosting maybe MS office, docker, Jenkins, etc., we basically need a hardware system and other resources.

The most crucial resource we need is the compute unit, the ram, and CPUs, and to store the OS program, we need memory i.e. HARD DISK. Today with a huge advancement in computing capabilities and computing requirements, the demand for resources has gone very high.


Supervisely is a web-platform which provides an environment to manage all the aspect, like Data collection, annotation, experiments with models, continuous model improvement, sharing, collaboration, in Deep Learning and Computer Vision project development process.

In this project, my objective is to create a model and train the same on an AWS agent.


Initially, we will find a team with one workspace and one member (you). Other members can be added as well but, we won’t be needing that.

Snapshot of the first page after signing up.

I created a workspace, named mlop_task_6.

Transfer learning is a machine learning method where a model developed for a task is reused as the starting point for a model on a second task.

It is a popular approach in deep learning where pre-trained models are used as the starting point on computer vision and natural language processing tasks given the vast compute and time resources required to develop neural network models on these problems and from the huge jumps in the skill that they provide on related problems.

TASK: To create a face recognition model using the VGG16 Model.

Vgg16 Model Architecture

VGG16 is a convolutional neural network model…

Deepti Tiwari

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