Skip to main content

Unix programming : tutorials.

The following set of tutorials reflects an effort to give Unix programmers and programmers wanna-be a chance to get familiar with various aspects of programming on Unix-like systems, without the need to buy an expensive set of books and spending a lot of time in understanding lots of technical material. The one assumption common to all tutorials (unless stated otherwise) is that you already know C programming on any system.

Comments

Popular posts from this blog

Fixing Unix/Linux/POSIX Filenames

Traditionally, Unix/Linux/POSIX filenames can be almost any sequence of bytes, and their meaning is unassigned. The only real rules are that "/" is always the directory separator, and that filenames can't contain byte 0 (because this is the terminator). Although this is flexible, this creates many unnecessary problems. In particular, this lack of limitations makes it unnecessarily difficult to write correct programs (enabling many security flaws), makes it impossible to consistently and accurately display filenames, causes portability problems, and confuses users. more ....

Learn perl.

What is Perl? Perl is Practical Extraction and Report Language. is used often to create interactive web pages, Perl is full programming language like C# and Java, to learn some of this language i uploaded a book which is free to use under the terms of GNU free documentation license!

Many Companies Hold Vast Data but Are Unprepared for LLM Fine-Tuning: How to Solve It and What to Do About It

  Many Companies Hold Vast Data but Are Unprepared for LLM Fine-Tuning: How to Solve It and What to Do About It In today’s data-driven world, companies across various industries generate and store vast amounts of data. From customer interactions and sales transactions to sensor readings and user-generated content, organizations are sitting on treasure troves of information. However, when it comes to leveraging this data for fine-tuning large language models (LLMs), many companies find themselves unprepared. The growing need for AI-powered solutions requires adapting these models to specific organizational needs—a task that demands both the right infrastructure and expertise. The Challenge: Vast Data, But Lacking Readiness for LLM Fine-Tuning Large language models, such as OpenAI’s GPT or Google’s Bert, have revolutionized industries by providing AI capabilities for natural language understanding, generation, and analysis. However, these models are typically pre-trained on generaliz...