A complete set of tables for writing in LaTeX which comprises:
The categories included in the TCL command list as a cheat sheet is presented below:
As we know, ML.NET is an open-source and cross-platform (Windows, macOS, Linux) machine learning framework in which you can create custom ML models using C# or F# without having to leave the .NET ecosystem.
ML.NET lets reusing all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps.
Moreover, it has been designed as an extensible platform so that you can consume other popular ML frameworks (TensorFlow, ONNX, Infer.NET, and more) and have access to even more machine learning scenarios, like image classification, object detection, and more.
Finally, according to Microsoft's tests, it has high performance and accuracy.
Using a 9GB Amazon review data set, ML.NET trained a sentiment analysis model with 95% accuracy. Other popular machine learning frameworks failed to process the dataset due to memory errors. Training on 10% of the data set, to let all the frameworks complete training, ML.NET demonstrated the highest speed and accuracy.
I will discuss the fundamentals of ML.NET, explore some sample codes, and explain the basics of the Microsoft Machine-Learning framework with a sample code.
C# and Python are one of the several popular programming languages because they are easy to learn, simple to use; moreover, they offer quality, performance, and fast development. Both C# and Python are object-oriented programming languages that aim to make them practical for real-world applications. However, some critical differences between them can help you decide which one is better for you to learn and use. This article discusses the differences between C# and Python by explaining when to use them and how they perform.
In this article, I will try to explain the basics and benefits of ML.NET. Firstly, the Types of Machine Learning have been discussed afterward the Architecture and High-Level Overview are considered, Finally the question "Why should we use ML.NET?" is answered.
Subnetting is the process of dividing one network into smaller networks. Collectively, the smaller networks are referred to as subnetworks (or subnets), and the singular subdivision is a subnetwork (more commonly referred to as a subnet). Every single computer that is connected to a subnet shares an identical portion of the IP address. This shared information is known as a routing prefix, and in IPV4 (Internet Protocol Version 4), the routing prefix is called a subnet mask. The subnet mask is a "quad-dotted decimal representation."
This IPv4 Subnet article can assist you in looking up how a network is broken up into subnets.
This article shares mnemonics and a chart for the International Morse Codes plus an Arduino code to say .... . .-.. .-.. --- / .-- --- .-. .-.. -..
This was the start of my journey in C#; it was delightful to code with standard design patterns and make scalable software.
Design patterns are solutions to software design problems you find again and again in real-world application development. Patterns are about reusable designs and interactions of objects.
Before diving into this article, it is highly recommended to look at Unified Modeling Language cheat sheet.
These are a compilation of publicly shared files of Do-Factory Gang Of Four, O'reilly Head First Design Patterns, Refactoring-Guru dive Into design patterns, and dive Into refactoring books with C# example projects.
This article is a concise image of application layers and four golden rules for keeping design patterns in mind while developing codes in general.