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šIn this guide, you will learn about the core concepts of serverless relevant for you as an ML engineer and you will also go on to deploy an image classification application on a serverless platform so you can see how easy and fast it is.
āļøYou can see more at the link at the end of the article. Thank you for your interest in the blog, if you find it interesting, please give me a like, comment and share with everyone. Thanks! ā¤ļø
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In this article, weāll discuss how to use jQuery Ajax for ASP.NET Core MVC CRUD Operations using Bootstrap Modal. With jQuery Ajax, we can make HTTP request to controller action methods without reloading the entire page, like a single page application.
To demonstrate CRUD operations ā insert, update, delete and retrieve, the project will be dealing with details of a normal bank transaction. GitHub repository for this demo project : https://bit.ly/33KTJAu.
Sub-topics discussed :
In Visual Studio 2019, Go to File > New > Project (Ctrl + Shift + N).
From new project window, Select Asp.Net Core Web Application_._
Once you provide the project name and location. Select Web Application(Model-View-Controller) and uncheck HTTPS Configuration. Above steps will create a brand new ASP.NET Core MVC project.
Letās create a database for this application using Entity Framework Core. For that weāve to install corresponding NuGet Packages. Right click on project from solution explorer, select Manage NuGet Packages_,_ From browse tab, install following 3 packages.
Now letās define DB model class file ā /Models/TransactionModel.cs.
public class TransactionModel
{
[Key]
public int TransactionId { get; set; }
[Column(TypeName ="nvarchar(12)")]
[DisplayName("Account Number")]
[Required(ErrorMessage ="This Field is required.")]
[MaxLength(12,ErrorMessage ="Maximum 12 characters only")]
public string AccountNumber { get; set; }
[Column(TypeName ="nvarchar(100)")]
[DisplayName("Beneficiary Name")]
[Required(ErrorMessage = "This Field is required.")]
public string BeneficiaryName { get; set; }
[Column(TypeName ="nvarchar(100)")]
[DisplayName("Bank Name")]
[Required(ErrorMessage = "This Field is required.")]
public string BankName { get; set; }
[Column(TypeName ="nvarchar(11)")]
[DisplayName("SWIFT Code")]
[Required(ErrorMessage = "This Field is required.")]
[MaxLength(11)]
public string SWIFTCode { get; set; }
[DisplayName("Amount")]
[Required(ErrorMessage = "This Field is required.")]
public int Amount { get; set; }
[DisplayFormat(DataFormatString = "{0:MM/dd/yyyy}")]
public DateTime Date { get; set; }
}
C#Copy
Here weāve defined model properties for the transaction with proper validation. Now letās define DbContextclass for EF Core.
#asp.net core article #asp.net core #add loading spinner in asp.net core #asp.net core crud without reloading #asp.net core jquery ajax form #asp.net core modal dialog #asp.net core mvc crud using jquery ajax #asp.net core mvc with jquery and ajax #asp.net core popup window #bootstrap modal popup in asp.net core mvc. bootstrap modal popup in asp.net core #delete and viewall in asp.net core #jquery ajax - insert #jquery ajax form post #modal popup dialog in asp.net core #no direct access action method #update #validation in modal popup
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Serverless M (or Serverless Modular) is a plugin for the serverless framework. This plugins helps you in managing multiple serverless projects with a single serverless.yml file. This plugin gives you a super charged CLI options that you can use to create new features, build them in a single file and deploy them all in parallel
Currently this plugin is tested for the below stack only
Make sure you have the serverless CLI installed
# Install serverless globally
$ npm install serverless -g
To start the serverless modular project locally you can either start with es5 or es6 templates or add it as a plugin
# Step 1. Download the template
$ sls create --template-url https://github.com/aa2kb/serverless-modular/tree/master/template/modular-es6 --path myModularService
# Step 2. Change directory
$ cd myModularService
# Step 3. Create a package.json file
$ npm init
# Step 3. Install dependencies
$ npm i serverless-modular serverless-webpack webpack --save-dev
# Step 1. Download the template
$ sls create --template-url https://github.com/aa2kb/serverless-modular/tree/master/template/modular-es5 --path myModularService
# Step 2. Change directory
$ cd myModularService
# Step 3. Create a package.json file
$ npm init
# Step 3. Install dependencies
$ npm i serverless-modular --save-dev
If you dont want to use the templates above you can just add in your existing project
plugins:
- serverless-modular
Now you are all done to start building your serverless modular functions
The serverless CLI can be accessed by
# Serverless Modular CLI
$ serverless modular
# shorthand
$ sls m
Serverless Modular CLI is based on 4 main commands
sls m init
sls m feature
sls m function
sls m build
sls m deploy
sls m init
The serverless init command helps in creating a basic .gitignore
that is useful for serverless modular.
The basic .gitignore
for serverless modular looks like this
#node_modules
node_modules
#sm main functions
sm.functions.yml
#serverless file generated by build
src/**/serverless.yml
#main serverless directories generated for sls deploy
.serverless
#feature serverless directories generated sls deploy
src/**/.serverless
#serverless logs file generated for main sls deploy
.sm.log
#serverless logs file generated for feature sls deploy
src/**/.sm.log
#Webpack config copied in each feature
src/**/webpack.config.js
The feature command helps in building new features for your project
This command comes with three options
--name: Specify the name you want for your feature
--remove: set value to true if you want to remove the feature
--basePath: Specify the basepath you want for your feature, this base path should be unique for all features. helps in running offline with offline plugin and for API Gateway
options | shortcut | required | values | default value |
---|---|---|---|---|
--name | -n | ā | string | N/A |
--remove | -r | ā | true, false | false |
--basePath | -p | ā | string | same as name |
Creating a basic feature
# Creating a jedi feature
$ sls m feature -n jedi
Creating a feature with different base path
# A feature with different base path
$ sls m feature -n jedi -p tatooine
Deleting a feature
# Anakin is going to delete the jedi feature
$ sls m feature -n jedi -r true
The function command helps in adding new function to a feature
This command comes with four options
--name: Specify the name you want for your function
--feature: Specify the name of the existing feature
--path: Specify the path for HTTP endpoint helps in running offline with offline plugin and for API Gateway
--method: Specify the path for HTTP method helps in running offline with offline plugin and for API Gateway
options | shortcut | required | values | default value |
---|---|---|---|---|
--name | -n | ā | string | N/A |
--feature | -f | ā | string | N/A |
--path | -p | ā | string | same as name |
--method | -m | ā | string | 'GET' |
Creating a basic function
# Creating a cloak function for jedi feature
$ sls m function -n cloak -f jedi
Creating a basic function with different path and method
# Creating a cloak function for jedi feature with custom path and HTTP method
$ sls m function -n cloak -f jedi -p powers -m POST
The build command helps in building the project for local or global scope
This command comes with four options
--scope: Specify the scope of the build, use this with "--feature" tag
--feature: Specify the name of the existing feature you want to build
options | shortcut | required | values | default value |
---|---|---|---|---|
--scope | -s | ā | string | local |
--feature | -f | ā | string | N/A |
Saving build Config in serverless.yml
You can also save config in serverless.yml file
custom:
smConfig:
build:
scope: local
all feature build (local scope)
# Building all local features
$ sls m build
Single feature build (local scope)
# Building a single feature
$ sls m build -f jedi -s local
All features build global scope
# Building all features with global scope
$ sls m build -s global
The deploy command helps in deploying serverless projects to AWS (it uses sls deploy
command)
This command comes with four options
--sm-parallel: Specify if you want to deploy parallel (will only run in parallel when doing multiple deployments)
--sm-scope: Specify if you want to deploy local features or global
--sm-features: Specify the local features you want to deploy (comma separated if multiple)
options | shortcut | required | values | default value |
---|---|---|---|---|
--sm-parallel | ā | ā | true, false | true |
--sm-scope | ā | ā | local, global | local |
--sm-features | ā | ā | string | N/A |
--sm-ignore-build | ā | ā | string | false |
Saving deploy Config in serverless.yml
You can also save config in serverless.yml file
custom:
smConfig:
deploy:
scope: local
parallel: true
ignoreBuild: true
Deploy all features locally
# deploy all local features
$ sls m deploy
Deploy all features globally
# deploy all global features
$ sls m deploy --sm-scope global
Deploy single feature
# deploy all global features
$ sls m deploy --sm-features jedi
Deploy Multiple features
# deploy all global features
$ sls m deploy --sm-features jedi,sith,dark_side
Deploy Multiple features in sequence
# deploy all global features
$ sls m deploy --sm-features jedi,sith,dark_side --sm-parallel false
Author: aa2kb
Source Code: https://github.com/aa2kb/serverless-modular
License: MIT license
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Recently, researchers from Google proposed the solution of a very fundamental question in the machine learning community ā What is being transferred in Transfer Learning? They explained various tools and analyses to address the fundamental question.
The ability to transfer the domain knowledge of one machine in which it is trained on to another where the data is usually scarce is one of the desired capabilities for machines. Researchers around the globe have been using transfer learning in various deep learning applications, including object detection, image classification, medical imaging tasks, among others.
#developers corner #learn transfer learning #machine learning #transfer learning #transfer learning methods #transfer learning resources
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In the past few years, especially after Amazon Web Services (AWS) introduced its Lambda platform, serverless architecture became the business realmās buzzword. The increasing popularity of serverless applications saw market leaders like Netflix, Airbnb, Nike, etc., adopting the serverless architecture to handle their backend functions better. Moreover, serverless architectureās market size is expected to reach a whopping $9.17 billion by the year 2023.
Global_Serverless_Architecture_Market_2019-2023
Why use serverless computing?
As a business it is best to approach a professional mobile app development company to build apps that are deployed on various servers; nevertheless, businesses should understand that the benefits of the serverless applications lie in the possibility it promises ideal business implementations and not in the hype created by cloud vendors. With the serverless architecture, the developers can easily code arbitrary codes on-demand without worrying about the underlying hardware.
But as is the case with all game-changing trends, many businesses opt for serverless applications just for the sake of being up-to-date with their peers without thinking about the actual need of their business.
The serverless applications work well with stateless use cases, the cases which execute cleanly and give the next operation in a sequence. On the other hand, the serverless architecture is not fit for predictable applications where there is a lot of reading and writing in the backend system.
Another benefit of working with the serverless software architecture is that the third-party service provider will charge based on the total number of requests. As the number of requests increases, the charge is bound to increase, but then it will cost significantly less than a dedicated IT infrastructure.
Defining serverless software architecture
In serverless software architecture, the application logic is implemented in an environment where operating systems, servers, or virtual machines are not visible. Although where the application logic is executed is running on any operating system which uses physical servers. But the difference here is that managing the infrastructure is the soul of the service provider and the mobile app developer focuses only on writing the codes.
There are two different approaches when it comes to serverless applications. They are
Backend as a service (BaaS)
Function as a service (FaaS)
Moreover, other examples of third-party services are Autho, AWS Cognito (authentication as a service), Amazon Kinesis, Keen IO (analytics as a service), and many more.
FaaS serverless architecture is majorly used with microservices architecture as it renders everything to the organization. AWS Lambda, Google Cloud functions, etc., are some of the examples of FaaS implementation.
Pros of Serverless applications
There are specific ways in which serverless applications can redefine the way business is done in the modern age and has some distinct advantages over the traditional could platforms. Here are a few ā
š¹ Highly Scalable
The flexible nature of the serverless architecture makes it ideal for scaling the applications. The serverless applicationās benefit is that it allows the vendor to run each of the functions in separate containers, allowing optimizing them automatically and effectively. Moreover, unlike in the traditional cloud, one doesnāt need to purchase a certain number of resources in serverless applications and can be as flexible as possible.
š¹ Cost-Effective
As the organizations donāt need to spend hundreds and thousands of dollars on hardware, they donāt need to pay anything to the engineers to maintain the hardware. The serverless applicationās pricing model is execution based as the organization is charged according to the executions they have made.
The company that uses the serverless applications is allotted a specific amount of time, and the pricing of the execution depends on the memory required. Different types of costs like presence detection, access authorization, image processing, etc., associated with a physical or virtual server is completely eliminated with the serverless applications.
š¹ Focuses on user experience
As the companies donāt always think about maintaining the servers, it allows them to focus on more productive things like developing and improving customer service features. A recent survey says that about 56% of the users are either using or planning to use the serverless applications in the coming six months.
Moreover, as the companies would save money with serverless apps as they donāt have to maintain any hardware system, it can be then utilized to enhance the level of customer service and features of the apps.
š¹ Ease of migration
It is easy to get started with serverless applications by porting individual features and operate them as on-demand events. For example, in a CMS, a video plugin requires transcoding video for different formats and bitrates. If the organization wished to do this with a WordPress server, it might not be a good fit as it would require resources dedicated to serving pages rather than encoding the video.
Moreover, the benefits of serverless applications can be used optimally to handle metadata encoding and creation. Similarly, serverless apps can be used in other plugins that are often prone to critical vulnerabilities.
Cons of serverless applications
Despite having some clear benefits, serverless applications are not specific for every single use case. We have listed the top things that an organization should keep in mind while opting for serverless applications.
š¹ Complete dependence on third-party vendor
In the realm of serverless applications, the third-party vendor is the king, and the organizations have no options but to play according to their rules. For example, if an application is set in Lambda, it is not easy to port it into Azure. The same is the case for coding languages. In present times, only Python developers and Node.js developers have the luxury to choose between existing serverless options.
Therefore, if you are planning to consider serverless applications for your next project, make sure that your vendor has everything needed to complete the project.
š¹ Challenges in debugging with traditional tools
It isnāt easy to perform debugging, especially for large enterprise applications that include various individual functions. Serverless applications use traditional tools and thus provide no option to attach a debugger in the public cloud. The organization can either do the debugging process locally or use logging for the same purpose. In addition to this, the DevOps tools in the serverless application do not support the idea of quickly deploying small bits of codes into running applications.
#serverless-application #serverless #serverless-computing #serverless-architeture #serverless-application-prosand-cons
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Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.
#machinelearningapps #machinelearningdevelopers #machinelearningexpert #machinelearningexperts #expertmachinelearningservices #topmachinelearningcompanies #machinelearningdevelopmentcompany
Visit Blog- https://www.xplace.com/article/8743
#machine learning companies #top machine learning companies #machine learning development company #expert machine learning services #machine learning experts #machine learning expert