{"slug": "my-experience-choosing-deployment-platforms-for-ml-projects", "title": "My Experience Choosing Deployment Platforms for ML Projects", "summary": "A developer shared their experience choosing deployment platforms for machine learning projects, highlighting Vercel for frontend, Hugging Face Spaces, Render, and Railway for backend, and GitHub for source code. They currently prefer Vercel for frontend, Railway for backend, and GitHub for source code, noting that the best choice depends on project requirements.", "body_md": "When deploying a Machine Learning project, choosing the right platform for the frontend, backend, and source code can make the process much easier.\n\nHere are some popular options I explored:\n\n🎨 Frontend Deployment\n\nVercel is one of my preferred choices for frontend deployment, especially for modern web applications.\n\nWhy I like it:\n\nEasy deployment\n\nGitHub integration\n\nAutomatic deployments\n\nGood performance\n\nSimple configuration\n\n⚙️ Backend Deployment\n\nHugging Face Spaces\n\nUseful for Machine Learning and AI applications\n\nSupports ML-focused deployments\n\nCan be convenient for demos and prototypes\n\nFree and paid options are available depending on the service and requirements\n\nRender\n\nSimple deployment process\n\nSupports backend applications\n\nProvides a free tier with limitations\n\nSuitable for smaller projects and prototypes\n\nRailway\n\nEasy backend deployment\n\nSupports databases and backend services\n\nConvenient for applications that need more resources\n\nUseful for ML-backed APIs depending on the model size and resource requirements\n\n💻 Source Code\n\nFor managing and sharing source code, I prefer GitHub.\n\nIt helps with:\n\nVersion control\n\nCollaboration\n\nProject documentation\n\nConnecting repositories to deployment platforms\n\nShowcasing projects to recruiters\n\n⭐ My Current Preference\n\nFor my projects, my preferred setup is:\n\n🎨 Frontend → Vercel\n\n⚙️ Backend → Railway\n\n💻 Source Code → GitHub\n\nThe best platform ultimately depends on the project's requirements, such as model size, RAM, CPU, database requirements, traffic, and budget.\n\nI'm currently learning more about deploying Machine Learning applications and comparing different cloud platforms. 🚀", "url": "https://wpnews.pro/news/my-experience-choosing-deployment-platforms-for-ml-projects", "canonical_source": "https://dev.to/kavya_g_0c3c44e363bf95383/my-experience-choosing-deployment-platforms-for-ml-projects-8j7", "published_at": "2026-08-10 13:56:37+00:00", "updated_at": "2026-08-10 14:16:37.050684+00:00", "lang": "en", "topics": ["machine-learning", "developer-tools"], "entities": ["Vercel", "Hugging Face Spaces", "Render", "Railway", "GitHub"], "alternates": {"html": "https://wpnews.pro/news/my-experience-choosing-deployment-platforms-for-ml-projects", "markdown": "https://wpnews.pro/news/my-experience-choosing-deployment-platforms-for-ml-projects.md", "text": "https://wpnews.pro/news/my-experience-choosing-deployment-platforms-for-ml-projects.txt", "jsonld": "https://wpnews.pro/news/my-experience-choosing-deployment-platforms-for-ml-projects.jsonld"}}