This article will explain the general architecture of a Convolution Neural Network (CNN) and thus helps to gain an understanding of how to classify images in different categories (different types of animals in our case) by writing a CNN model from scratch using PyTorch.
Complete Code Links
Step 1: (Downloading Dataset)
A full stack developer is a web developer or engineer who works with both the front and back ends of a website or application — meaning they can tackle projects that involve databases, building user-facing websites, or even work with clients during the planning phase of projects.
A full stack application combined with Docker and following a microservice & RESTful architecture can do wonders in any development, testing or even production environment.
In this blog we will create a full stack Notes taking application in a proper manner using various tools.
In this article we will experience the magic of docker-compose by using it to combine multiple docker images. Consider an environment where you want to Up, Run or Manage several Docker Containers such that they shares the same network, or uses a common volume etc. All this can be done with the help of docker-compose.
This article assume you have a basic understanding of Docker environment (images, containers etc). If not please check out my previous article about Docker first.
Also See (Next Part of this series)
Introduction to Docker-Compose
The overall blog is divided into three parts
Part 2: Queries & Operations in ElasticSearch on various Indexes & Documents (you are here…)
Part 3: Comming Soon…
In part 1, you must have familiarized yourself with basic terms like indexes, documents etc and at this point your ElasticSearch & Kibana must be up and running.
If not then please check out the Part 1 of this editorial before continuing to this.
Enough talk, lets open the Kibana Dev tools dashboard & hit with the following queries.
Part 1: Introduction & Running Up ElasticSearch & Kibana (you are here…)
Part 3: Comming Soon…
What is ElasticSearch
Elasticsearch is a search engine based on Lucene library. It is a distributed RESTful search engine with an HTTP web interface and schema-free JSON documents.
Why ElasticSearch ?
In a nutshell: Write Code Once -> Create Docker Container -> Run Anywhere