Yu Shu

🚀 FresHeat – Fresh Food (ReactJS Project) 🔗 Live Demo → https://lnkd.in/ghbp4Uu9 💻 GitHub Repository → https://lnkd.in/gcUfvdnk I’m excited to share my project FresHeat, a modern and responsive fresh-food web application built with React.js. This project focuses on creating an intuitive user experience, clean UI, and scalable front-end architecture. 🔍 Key Features:- 1. Responsive UI/UX — Optimized for mobile, tablet, and desktop devices. 2. Dynamic State Management — Implemented using React hooks (useState , useEffect ) for smooth UI updates. 3. Component-Based Architecture — Modular and reusable components (Navbar, Product Cards, Footer, etc.). 4. Navigation & Routing — Seamless page transitions using React Router. 5. Deployed on Netlify — End-to-end delivery with live hosting. 🛠️ Tech Stack Frontend: React.js, JavaScript (ES6+), JSX Styling: Bootstrap, CSS3, Responsive Design Deployment: Netlify Tools: VS Code, Git & GitHub for version control 🌱 Learnings & Takeaways 1. Designing scalable component structures in React 2. Implementing state and event handling for interactive UI 3. Ensuring responsive layouts with Bootstrap + custom CSS 4. Deploying and managing a React app in production 🙏 Special Thanks A big thank you to Hemant Bhalerao & Envision Computer Training Institute Pvt. Ltd. for guiding me throughout this learning journey. Your mentorship played a key role in helping me build confidence in React.js and modern front-end development. 💡 This project strengthened my React fundamentals and gave me hands-on experience with building a real-world, responsive web app. #ReactJS #JavaScript #WebDevelopment #FrontendDevelopment #Coding #ProgrammersLife #WebDesign #Bootstrap #CSS3 #HTML5 #Netlify #GitHub #TechProjects #ResponsiveDesign #SoftwareEngineering #100DaysOfCode #DevCommunity

1,762

108 Comments

. 🚀 TaskFlow – MERN Stack Task Manager 🔗 Live App: https://lnkd.in/gtei_iDh 💻 Source Code: https://lnkd.in/gB5pQDkZ I’m excited to share TaskFlow, a full-stack task management application built to explore real-world authentication, session handling, and production deployment challenges using the MERN stack. 🧰 Tech Stack • React (Vite) + Tailwind CSS • Node.js & Express.js • MongoDB Atlas • Google OAuth 2.0 (Passport.js) • Session & cookie-based authentication • Deployed on Vercel (Frontend) & Render (Backend) ✨ Key Features • Google Sign-In with OAuth 2.0 • Secure sessions with HTTP-only cookies • Protected routes & auth status validation • Responsive UI with reusable layouts • Full CRUD task management • Environment-based production configuration 📚 What I Learned • OAuth redirect handling in production • Cross-domain cookies & CORS configuration • Session persistence after deployment • Clean React architecture using Context & Layouts • Debugging real hosting issues (not just localhost) This project pushed me beyond tutorials and helped me understand how production-grade web apps actually work. Feedback and suggestions are welcome 🙌 #MERNStack #ReactJS #NodeJS #MongoDB #GoogleOAuth #PassportJS #FullStackDevelopment #WebDeveloper #LearningByBuilding

7

Oracle Expands AWS, Azure, and Google Cloud Partner Programs Oracle has enhanced its multi-cloud strategy by introducing new AI features and partner programs for Oracle Database on AWS, Azure, and Google Cloud. Central to this update is the Oracle AI Database 26ai, designed to deliver AI-powered database performance across these cloud platforms. Oracle Database@AWS facilitates easy migration of Oracle Exadata workloads to AWS while maintaining on-premises-level performance, leveraging Oracle Real Application Clusters (RAC) and zero ETL integration to connect data with Amazon Bedrock’s generative AI service. Partners in both the AWS Partner Network and Oracle PartnerNetwork can now resell Oracle Database@AWS through the AWS Channel Partner Private Offer, allowing customized pricing and contracts. Oracle plans to expand service availability to about 20 regions, starting with several key global locations. Oracle Database@Azure operates in 28 regions with five more planned for next year. A new partner program enables reselling Oracle Database@Azure on the Microsoft Marketplace, allowing AI analytics directly where Oracle data resides and integration with Microsoft AI services like Fabric, Copilot, and Azure AI Foundry. Oracle aims to expand AI-embedded database capabilities to reduce latency and costs related to data movement. Oracle Database@Google Cloud now includes AI-embedded features and partner programs permitting Google Cloud partners to resell or integrate the service. Customers can utilize Oracle Database 19c, AI Database 26ai, Oracle RAC, Exadata, and Autonomous AI Database within Google Cloud. Oracle and Google plan to accelerate AI-driven data innovation through the Exascale infrastructure-based Oracle Exadata Database Service, Base Database Service, and Autonomous AI Lakehouse, combining Google Cloud AI tools with Oracle database technology for cross-cloud data use. With these updates, Oracle is advancing toward completing its multi-cloud strategy, enabling customers to use Oracle AI Database features in their preferred cloud environments without data movement and empowering partners to access new opportunities through cloud marketplaces. Oracle expressed commitment to ongoing collaboration with major cloud providers to grow the global AI-embedded database ecosystem. #CloudComputing #SouthKorea https://lnkd.in/gwhkUNbd

3

The first lesson in my frontend-to-DE transition: you can't just run numbers — you have to explain them. My mentor wouldn't let me touch Dagster UI. He wanted me to understand the pipeline from the ground up. As a frontend developer, I chose the way I know best — build a Streamlit Dashboard. 5 pages dissecting a medical-grade CGM pipeline I designed myself (synthetic data, no real patient data): Page 1 — Opened the data, found 110K rows missing (10.5% gap) Page 2 — Saw 35.6x Data Skew, broke it down to just 2.9x Page 3 — Understood FDA imputation rules, and why Linear Interpolation = 0 Page 4 — A million rows JOINed into 90 through aggregation Page 5 — One asset consuming 90% of pipeline time Biggest win? I can now explain where every number comes from. Biggest gap? I still can't manipulate this data in code. The Dashboard gave me "data intuition" — next step is turning intuition into coding ability. For anyone making a similar transition: start with the tools you know. Wrap the unfamiliar with the familiar — the learning curve flattens considerably. https://lnkd.in/ghfSkntq #DataEngineering #CareerTransition #Streamlit #Polars #HealthTech #CGM #DataPipeline #FrontendToDe #Python #Parquet #MedTech #GLP1 #Dagster #PartitionPruning #DataSkew

5