Yet another structural engineer who is passionate about computer programming, reverse engineering, and machine learning. This blog aims to share the experience, knowledge, papers, and valuable resources.
I have read, watched, and been through all of the articles I create, so if there are any questions related to them, feel free to comment on the underlying page or Contact Me.
The equation is a vital part of many technical manuscripts, including thesis and research papers. However, typing it in Microsoft Word is an arduous task. To cope with it, Microsoft Word introduced the LaTeX type equation editor feature which is termed "Math AutoCorrect" and is available since Microsoft Word 2007.
This article aims to elaborate on the most usages of the Microsoft Word equation editor.
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 .... . .-.. .-.. --- / .-- --- .-. .-.. -..
The below Youtube channels are highly recommended for bachelors since they will help to understand and visualize the semantics of math.