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React Native is an excellent choice for building mobile applications, including chat apps, due to its cross-platform capabilities and extensive community support. In this guide, we will walk through the process of creating a chat app for Android using React Native. By the end, you’ll have a functional messaging app that can send and receive messages in real-time. Prerequisites Before starting, ensure you have the following installed: Node.js React Native CLI Android Studio (for emulator or physical device testing) Firebase ... How To Build A React Native Chat App For Android
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Artificial Intelligence (AI) is revolutionizing the way enterprises operate, but Large Language Models (LLMs) have inherent limitations in accuracy, automation, and decision-making. Retrieval Augmented Generation (RAG) and AI Agents address these gaps by improving factual consistency, optimizing workflows, and enabling more informed decisions. This article explores how these technologies enhance enterprise AI with code examples to illustrate their impact. Understanding Retrieval Augmented Generation (RAG) What is RAG? Retrieval Augmented Generation (RAG) is a technique that combines retrieval-based models with generative ... How Retrieval Augmented Generation and AI Agents Improve Enterprise AI
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Data lakes have become a central component of modern data architectures, enabling organizations to store vast amounts of structured, semi-structured, and unstructured data. However, managing, querying, and ensuring the reliability of data lakes pose significant challenges. Apache Doris and Apache Iceberg are two open-source projects that are redefining how data lakes work by enhancing performance, manageability, and analytical capabilities. Understanding Apache Doris Apache Doris is a high-performance, real-time analytical database that is designed for interactive queries and high-throughput analytical workloads. ... How Apache Doris and Iceberg Are Redefining the Way Data Lakes Work
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Django is a powerful web framework that enables developers to build robust applications quickly. However, improper use of Django’s features can lead to messy dependencies and bloated views, making applications difficult to maintain and scale. This article explores common mistakes that contribute to these issues, along with solutions and best practices. 1. Overloading Views with Business Logic One of the most common mistakes in Django development is placing too much logic inside views. This leads to tightly coupled code, making ... Common Django Mistakes That Cause Messy Dependencies and Logic-Heavy Views
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Microsoft Graph API is a powerful unified endpoint for accessing and managing various Microsoft 365 services, including users, groups, devices, and security features. With RESTful principles and OAuth 2.0 authentication, administrators can efficiently manage user identities, groups, and devices programmatically. Introduction to Microsoft Graph API Microsoft Graph API enables developers and IT administrators to interact with Microsoft 365 services using a single endpoint: https://graph.microsoft.com. It supports a wide range of functionalities, including: User identity management Group administration Device management Security ... Effective Administration of User Identities, Groups, and Devices with Microsoft Graph REST API
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Cloudflare Pages provides a powerful platform for deploying serverless applications, and when combined with Next.js, NextAuth, D1 (Cloudflare’s SQL database), and Prisma, you can build a robust, serverless authentication system with minimal hassle. This guide will walk you through the entire process, from setting up your environment to deploying a functional authentication system. Prerequisites Before we begin, ensure you have the following: A Cloudflare account Node.js and npm installed A Next.js project set up Prisma installed A Cloudflare Pages project ... How To Set Up A Serverless Sign-In Solution on Cloudflare Pages Using Next.js, NextAuth, D1, and Prisma
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In today’s data-driven world, data scientists use multiple programming languages, frameworks, and tools to build robust analytical models. However, one major challenge in data science is integrating multiple languages within a distributed environment. This article explores how to build a distributed multi-language data science system, covering architecture, coding examples, and best practices. Why Multi-Language Support in Data Science? Different programming languages excel in different aspects of data science. Python dominates for its rich ecosystem and ease of use, R excels ... Building a Distributed Multi-Language Data Science System
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Security should be a fundamental aspect of the software development lifecycle (SDLC), not an afterthought. Integrating security into the development phase can significantly reduce vulnerabilities and the risk of exploitation. Two crucial methods to achieve this are Threat Modeling and Static Analysis. These techniques help identify and mitigate potential security threats early in the development process. In this article, we will discuss how to integrate security into the development phase using threat modeling and static analysis, with practical examples. What ... How To Integrate Security Into The Development Phase With Threat Modeling And Static Analysis
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Building a scalable and distributed e-commerce platform is essential for handling high traffic loads, ensuring fault tolerance, and providing a seamless customer experience. AWS offers a suite of services that help in architecting such a platform with modular services and scalable components. This article delves into the architectural design, key AWS services, and code examples for implementing a distributed e-commerce system. High-Level Architecture Overview A distributed e-commerce platform consists of multiple interconnected services that work together to provide functionalities such ... The Architecture of a Distributed and Scalable E-Commerce Platform on AWS
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AWS provides powerful GPU instances that allow users to train and deploy deep learning models efficiently. By installing CUDA, containerizing the model, and leveraging AWS container orchestration services like ECS (Elastic Container Service) or EKS (Elastic Kubernetes Service), you can scale your workloads effectively. This guide walks through these steps with coding examples. Installing CUDA on AWS GPU Instances AWS provides GPU-enabled EC2 instances, such as p3 and g4 instances, which support NVIDIA GPUs. To utilize these GPUs, you need ... How To Install CUDA On AWS GPU Instances, Containerize Your Deep Learning Model, And Scale With ECS/EKS
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Garbage collection (GC) plays a crucial role in Java’s memory management by automatically reclaiming unused objects and preventing memory leaks. However, selecting the right garbage collector can significantly impact an application’s performance, affecting response time, throughput, and memory usage. In this article, we will explore different garbage collectors in Java, their use cases, and how to choose the best one for optimal performance. Understanding Java Garbage Collection Garbage collection in Java is managed by the Java Virtual Machine (JVM). The ... How To Choose The Right Garbage Collector In Java For Optimal Performance
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Implementing a chat history feature is crucial for developing conversational AI applications, as it maintains context and enhances user experience. By leveraging Azure Cosmos DB for NoSQL with the Go SDK and integrating it with LangChainGo, developers can efficiently manage and retrieve chat histories. This article provides a comprehensive guide to building such an implementation, complete with coding examples. Prerequisites Before diving into the implementation, ensure you have the following: Azure Subscription: An active Azure account. If you don’t have ... How To Build A Chat History Implementation With Azure Cosmos DB For NoSQL Go SDK And LangChainGo