Posted on

Create a REST API in C# Using ChatGPT

ChatGPT is a cutting-edge natural language processing model created by OpenAI, an artificial intelligence research center founded by Elon Musk, Sam Altman, and Greg Brockman. The model was announced in June 2018, and has continuously been modified and upgraded, with the most recent version, GPT-3, being released in 2020. ChatGPT was made from GPT-3, and was released back in 2022. The “GPT” in ChatGPT stands for “Generative Pre-trained Transformer,” a reference to the model’s deep learning architecture. ChatGPT essentially uses massive amounts of text data to “learn” the intricacies of human language, allowing it to create replies that are frequently impossible to differentiate from those of humans. The ChatGPT technology is based on a type of neural network known as a transformer, which is well-suited to natural language processing applications. C#

ChatGPT’s capacity to create high-quality output to a wide range of prompts you give in the chat box is one of its key features. The response you get feels like it has been generated by a human. You can also specify the conditions of your request. The model was trained on a vast corpus of text, so it can rely on a wide range of data to answer questions, provide information, or participate in casual conversation generated from its neural network. It is crucial to remember; however, that ChatGPT is not flawless. When faced with suggestions that are beyond the model’s area of knowledge, the model may provide illogical or unsuitable replies. ChatGPT usage is sometimes high, and, because of this, there can sometimes be a limit to how many queries you can send. 

Posted on

C# Coding Convention: Coding Standard in C#

Coding conventions are a set of guidelines for writing code that is consistent, readable, and comprehensible. They are also sometimes called programming conventions, style guides, or coding standard. These conventions cover various aspects of the code, such as naming conventions, indentation, commenting, and formatting. By following these conventions, developers can quickly understand the structure and purpose of the code, which makes it easier to debug and maintain the code. Additionally, conventions ensure the code is consistent across a team or organization, which can improve collaboration and communication among developers.

The term “clean code” refers to a programming style that also prioritizes maintainability and scalability by following principles like clarity, simplicity, consistency, and modularity. Clean code is important for the main developers and other developers who will read and maintain it in the future. Writing it requires discipline and attention to detail, but the benefits are well worth the effort. It can improve the speed and efficiency of development, reduce bugs and errors, and make the codebase more scalable and maintainable.

Posted on

Petastorm: A Simple Approach to Deep Learning Models in Apache Parquet Format

Petastorm, an open-source data access library, enables single-node or distributed training as well as evaluation of deep learning models precisely from datasets in Apache Parquet format and datasets that are already loaded as Apache Spark DataFrames. As Andrey, a U.S.-based Python engineer, notes, it supports popular Python-based machine learning (ML) frameworks including Tensorflow, PyTorch, and PySpark. For more information about Petastorm, refer to the Petastorm GitHub page and Petastorm API documentation.

Petastorm enables either single machine or distributed training, as well as support for multiple Python-based ML frameworks such as NumPy, Tensorflow, Theano, Pytorch, and PySpark. It is the go-to library for the evaluation of deep learning models using Apache Parquet formatted datasets.