Vitalii Sventyi

Preventing Server Downtime After Updates

Deploying updates is a necessary part of software development, but it can be a nerve-wracking experience. Developers often hold their breath, hoping that the new code won’t bring the servers to their knees. Server downtime after a major update can be devastating. It frustrates users, damages reputation, and impacts business significantly. This article will explore some common causes of these issues and look at some best practices in DevOps that can help you avoid those midnight panic calls.

What Is Recursion in Programming: A Beginner’s Guide

Recursion can be one of the most challenging concepts for beginners to grasp in programming. It’s often used in problem-solving, especially for tasks that involve repetitive or nested structures, like computing mathematical sequences, navigating trees, or solving puzzles. Simply put, recursion is a way for a function to call itself.

PgBouncer in Django: What It Is and Why We Need It

Scaling Django applications means dealing with many database connections. Each request to the database opens a new connection. This is costly for memory, CPU, and database resources, especially under heavy loads. PgBouncer is a lightweight connection pooler for PostgreSQL. It helps manage these connections efficiently by reusing them, reducing the overhead caused by opening and closing connections for each request.

SQL vs NoSQL Databases: Which One Should You Choose?

Choosing the right database for your project is a crucial decision. It can affect the scalability, performance, and complexity of your system. Today, we explore two primary database types: SQL and NoSQL. Each comes with unique benefits and challenges, making one more suitable than the other in certain scenarios. Let’s break them down so you can make an informed choice for your needs.

How to Fine-Tune a Large Language Model in AI: A Simple Guide

Fine-tuning a large language model (LLM) in AI might sound complex, but it can be broken down into simple steps. This guide will explain how you can adjust these powerful tools to better meet your needs. We will use easy-to-understand language to make the process clear.

Step-by-Step Guide to Building a Simple Chat Application with GPT-4o-mini API

This guide explains how to create a simple chat application using the OpenAI API and Flask, a Python web framework. You'll learn to set up your development environment, integrate the OpenAI API for generating responses, and build a web interface for user interaction.

What is DSPy and How to Get Started Using It

DSPy is emerging as a game-changer for optimizing language model (LM) prompts and weights in the rapidly evolving field of AI. It stands for Declarative Self-improving Language Programs, pythonically. DSPy simplifies the complex process of integrating and fine-tuning LMs in a pipeline, making it easier to achieve high-quality results with less manual intervention.

How to Deploy a Docker App to AWS?

Imagine you've built a stunning application using Docker. Now, you want to share it with the world by deploying it to AWS (Amazon Web Services). Sounds intriguing, right? In this guide, we'll walk through the steps to get your Docker app up and running on AWS smoothly. You'll feel like a tech wizard in no time!

Why Should You Normalize Data in Machine Learning?

Normalization of data is a fundamental concept in machine learning that is often overlooked by beginners, leading to suboptimal model performance and inaccurate predictions. In simple terms, data normalization is the process of scaling and standardizing the input data in a consistent and uniform manner. But why is this normalization step so crucial in the realm of machine learning, and what consequences can arise if it is neglected?

Tackling the Scale: What Is Class Imbalance in Machine Learning?

Imagine you're on a seesaw, and on one end, there's a big ol' elephant, and on the other end, there's a tiny mouse. Clearly, the seesaw's going to be pretty lopsided, right? Well, class imbalance in machine learning is a bit like that seesaw. It's what happens when the classes in your data aren't represented equally, causing the scales to tip in favor of one class over the others.

Do You Need a Windows Computer to Run LLaMA?

When it comes to state-of-the-art AI models, LLaMA has been making waves in the tech community. With the ever-expanding capabilities of AI, many individuals and businesses are eager to explore what these advanced tools can offer. A common question that pops up is whether a Windows computer is necessary to dive into the world of LLaMA. Let's explore this topic and uncover some interesting facets of operating systems and AI compatibility.

Exploring PyTorch: Your Gateway to Machine Learning

PyTorch is an open-source machine learning library for Python, used for applications such as natural language processing. It's known particularly for its flexibility and speed, especially in comparison to its peers. What truly sets PyTorch apart is its use of dynamic computation graphs. In Layman's terms, this means PyTorch allows you to change how your model behaves on-the-fly, unlike other libraries that use static graphs where the model's behavior is set before it even runs.

What Hardware Do I Need To Run LLaMa?

When we talk about running the latest AI models like LLaMa (Large Language Model), the excitement is palpable. After all, these models promise cutting-edge performance in tasks like text generation, language translation, and even answering complex queries. Yet, amid the buzz, a crucial question arises: What hardware do I need to effectively run LLaMa? If you're planning to dive into the fascinating world of AI and machine learning with LLaMa, here’s a straightforward guide to help you set up the right hardware.

How to Install LLaMa 3 on Your Computer

Meta has introduced LLaMa 3, their latest Large Language Model. This model offers a dynamic tool for individuals, creators, researchers, and businesses. LLaMa 3 features models ranging from 8 billion to 70 billion parameters, providing diverse capabilities for various applications. This guide outlines the steps required to install LLaMa 3 on your computer.

Building a RAG System with OpenVINO and LangChain

A RAG (Retrieval-Augmented Generation) system is a cutting-edge tool in the world of artificial intelligence (AI) that enhances the capabilities of language models by combining data retrieval with text generation. This approach not only generates more accurate and contextually relevant answers but also opens up new possibilities for creating smarter AI systems. In this tutorial, we will explore a step-by-step guide on how to set up a RAG system using OpenVINO, an AI performance toolkit from Intel, and LangChain, a library for building language model applications.

Ditch Unwanted Local Changes and Master GitHub Commands

Are you a developer tangled in a web of changes that didn't turn out as expected? Sometimes you're coding away, and you realize—the changes you've made are a complete fiasco. It's like knitting a scarf, only to accidentally drop a stitch and see your beautiful pattern unravel before your eyes. When you're using Git, the version control superstar, it's not the end of the world. Say hello to a quick undo button for your code!

RAG vs. Fine-Tuning in AI Training

In AI, teaching computers to talk and write like humans is a big challenge. Two common ways to do this are Retrieval-Augmented Generation (RAG) and fine-tuning. Each has its good and bad points, making them fit for different AI tasks. We'll look at these methods, breaking down their advantages and disadvantages in easy words.

The Role of Embedding Models in Retrieval Augmented Generation

Imagine you're writing a story and get stuck at some point. You might go back to your favorite book or the internet to find inspiration or gather more information. Similarly, Retrieval Augmented Generation (RAG) allows AI models to look up relevant information while generating text. It's like the AI has access to a vast library of information it can search through to make its output more accurate and informative.