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ASP.NET Core Razor Pages + Machine Learning (Project Based)

  • Development
  • Jan 30, 2025
SynopsisASP.NET Core Razor Pages + Machine Learning (Project Based ,...
ASP.NET Core Razor Pages + Machine Learning (Project Based)  No.1

ASP.NET Core Razor Pages + Machine Learning (Project Based), available at $49.99, has an average rating of 4.07, with 26 lectures, based on 7 reviews, and has 68 subscribers.

You will learn about Create ASP .NET Core Razor Pages web application from scratch. Create a Machine Learning Model in .NET/.NET CORE Consume a Machine Learning model from an ASP .NET Core Razor Pages web application Get used to Dependency Injection and repository pattern Understand and use EntityFrameworkCore This course is ideal for individuals who are If you are interested to learn ASP .NET Core razor pages and use it to build great web apps or Developers who want to easily integrate machine learning capabilities to their C# applications or .NET developers wanting to learn ML .NET It is particularly useful for If you are interested to learn ASP .NET Core razor pages and use it to build great web apps or Developers who want to easily integrate machine learning capabilities to their C# applications or .NET developers wanting to learn ML .NET.

Enroll now: ASP.NET Core Razor Pages + Machine Learning (Project Based)

Summary

Title: ASP.NET Core Razor Pages + Machine Learning (Project Based)

Price: $49.99

Average Rating: 4.07

Number of Lectures: 26

Number of Published Lectures: 26

Number of Curriculum Items: 26

Number of Published Curriculum Objects: 26

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

  • Create ASP .NET Core Razor Pages web application from scratch.
  • Create a Machine Learning Model in .NET/.NET CORE
  • Consume a Machine Learning model from an ASP .NET Core Razor Pages web application
  • Get used to Dependency Injection and repository pattern
  • Understand and use EntityFrameworkCore
  • Who Should Attend

  • If you are interested to learn ASP .NET Core razor pages and use it to build great web apps
  • Developers who want to easily integrate machine learning capabilities to their C# applications
  • .NET developers wanting to learn ML .NET
  • Target Audiences

  • If you are interested to learn ASP .NET Core razor pages and use it to build great web apps
  • Developers who want to easily integrate machine learning capabilities to their C# applications
  • .NET developers wanting to learn ML .NET
  • At the end of this course you will be ready to work on any project of ASP .Net Core Razor Pages. You will learn how create and use machine learning models for .NET applications and you will also get other skills which will be very useful to your career moving forward. These includes but not limited to designing and working with SQL Databases,Entity Framework Core, services(interfaces and repositories),dependency injection and many more.

    There are many benefits of having the skills that will be offered in this course. Firstly, knowing how to use ASP .Net Core will help you to create enterprise applications that are cross platform(i.e can be deployed or hosted in any operating system(OS), not just Windows OS alone). This course will help you to easily create Machine Learning models in .NET environment using C# , using machine learning models created in .NET to .NET applications is very easy as compared to integrating models developed by other frameworks. In this course you will also learn how to work with SQL databases which is very essential for every software developer. Most businesses use SQL databases data for their systems.

    The first thing we are going to do in this course is to learn how to use Materialize CSS so that we can be able to make the appearance of our application to be great. After this section we are going to create our first project of ASP .Net Core Razor Pages. We are going to use object oriented programming practices to develop our web application. It is in this section where you are going to learn a lot about ASP .NET Core Razor Pages. Then, we are going to move to the next section where we are going to create a Console Application for machine learning purposes. The end result of this section will be a machine learning model. In our last section we are going consume our machine learning model created in the previous section.

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Introduction

    Lecture 2: Project Demo

    Chapter 2: Materialize CSS and static files

    Lecture 1: Download and browse static files

    Lecture 2: Learning Material Design with Materialize CSS

    Chapter 3: ASP.NET Core Razor Pages Web Application

    Lecture 1: Introduction to ASP.NET Core Razor Pages project

    Lecture 2: Create ASP.NET Core Razor Pages Web Application

    Lecture 3: Change Navigation Bar Styling

    Lecture 4: Create A Data Model

    Lecture 5: Create Database+Migrations+new database table

    Lecture 6: Create DiaryEntry interface

    Lecture 7: Create DiaryEntry repository

    Lecture 8: Configuring Services in StartUp file

    Lecture 9: Add diary entry input with client side validation

    Lecture 10: Add OnPost action method for saving diary entry

    Lecture 11: Display diary entries using partial pages

    Lecture 12: Implement Delete Functionality

    Lecture 13: Edit(update) razor page witn OnGet method

    Lecture 14: Add OnPost method for updating diary entry

    Chapter 4: Machine Learning for .NET (ML.NET)

    Lecture 1: Introduction to Machine Learning using ML.NET

    Lecture 2: Console Application for Machine Learning

    Lecture 3: Load data to the Console application

    Lecture 4: Build and train machine learning model

    Lecture 5: Evaluate accurancy of the Machine Learning model

    Lecture 6: Save Machine Learning Model for later use

    Chapter 5: ASP.NET Core Razor Pages with Machine Learning

    Lecture 1: Add Machine Learning to ASP.NET Core Razor Project

    Lecture 2: Applying Machine Learning to ASP.NET Core Razor Pages

    Instructors

  • ASP.NET Core Razor Pages + Machine Learning (Project Based)  No.2
    Linda Mazibuko
    Senior Software Developer at EasyLearn Technologies
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  • 2 stars: 1 votes
  • 3 stars: 2 votes
  • 4 stars: 1 votes
  • 5 stars: 3 votes
  • Frequently Asked Questions

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