{"id":268799,"date":"2025-05-27T11:28:57","date_gmt":"2025-05-27T11:28:57","guid":{"rendered":"https:\/\/imarticus.org\/blog\/?p=268799"},"modified":"2025-06-03T11:57:27","modified_gmt":"2025-06-03T11:57:27","slug":"how-to-deploy-machine-learning-models-on-aws-ec2-beginners-guide","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/how-to-deploy-machine-learning-models-on-aws-ec2-beginners-guide\/","title":{"rendered":"How to Deploy Machine Learning Models on AWS EC2: Beginner\u2019s Guide"},"content":{"rendered":"<p><i><span style=\"font-weight: 400;\">Are You Still Struggling to Launch <\/span><\/i><b><i>Machine Learning Model Deployment<\/i><\/b><i><span style=\"font-weight: 400;\"> Live?<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">Ever trained a brilliant model but couldn\u2019t figure out how to get it into users\u2019 hands? You\u2019re not alone. Many data science learners and early professionals get stuck between \u201ctraining\u201d and \u201cdeployment.\u201d Knowing <\/span><b>how to deploy machine learning models <\/b><span style=\"font-weight: 400;\">effectively is what turns your code into something valuable and deployable.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this beginner\u2019s guide, we\u2019ll walk you through a complete process to deploy ML models on AWS EC2 from scratch. You\u2019ll also learn how the <\/span><b>Programme in Data Science and Artificial Intelligence<\/b><span style=\"font-weight: 400;\"> helps bridge this skill gap.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Why Machine Learning Model Deployment Matters in Real Projects<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Training a model is half the battle. If it just sits on your laptop, it serves no one. Model deployment helps you:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Make real-time predictions<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Allow others to use your model via a web or mobile app<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Turn your portfolio project into a product<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Learn backend basics that hiring managers love<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">With cloud platforms like AWS EC2, this is easier than ever, even if you\u2019re just getting started.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Understand EC2: The Backbone of AWS Deployment<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Amazon EC2 (Elastic Compute Cloud) gives you resisable computing capacity in the cloud. That means you can rent a server, use it like your computer, and run ML apps on it.<\/span><\/p>\n<p><a href=\"https:\/\/en.wikipedia.org\/wiki\/Amazon_Elastic_Compute_Cloud\"><span style=\"font-weight: 400;\">Amazon Elastic Compute Cloud<\/span><\/a><span style=\"font-weight: 400;\"> is a service within Amazon Web Services (AWS) that enables users to rent virtual servers to run their own computing applications.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Common AWS EC2 Instance Types for ML Workloads<\/span><\/h3>\n<table>\n<thead>\n<tr>\n<th><b>EC2 Instance Type<\/b><\/th>\n<th><b>Best For<\/b><\/th>\n<th><b>Features<\/b><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\">t2.micro<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Beginners, testing<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Free tier, low performance<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">g4dn.xlarge<\/span><\/td>\n<td><span style=\"font-weight: 400;\">GPU-based inference<\/span><\/td>\n<td><span style=\"font-weight: 400;\">NVIDIA GPU, 16 GB RAM<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">m5.large<\/span><\/td>\n<td><span style=\"font-weight: 400;\">General-purpose workloads<\/span><\/td>\n<td><span style=\"font-weight: 400;\">8 GB RAM, 2 vCPUs<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">p3.2xlarge<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Deep learning training<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Powerful GPU, expensive<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">c5.large<\/span><\/td>\n<td><span style=\"font-weight: 400;\">High performance compute<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Best for CPU-intensive tasks<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><span style=\"font-weight: 400;\">Choosing the right EC2 type depends on your budget and task type. Most beginners start with t2.micro or m5.large.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Step-by-Step Guide to Machine Learning Model Deployment on AWS EC2<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">According to data from <\/span><a href=\"https:\/\/www.crn.com\/news\/cloud\/2025\/cloud-market-share-q1-2025-aws-dips-microsoft-and-google-show-growth\"><span style=\"font-weight: 400;\">Synergy Research Group<\/span><\/a><span style=\"font-weight: 400;\">, enterprises worldwide spent $94 billion on cloud infrastructure services in the first quarter of 2025.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">1. Train Your ML Model Locally<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Train your model in Jupyter Notebook or VS Code. Export it using joblib or pickle.\u00a0<\/span><\/p>\n<p><i><span style=\"font-weight: 400;\">You\u2019ll need:<\/span><\/i><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Preprocessed data<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Trained model file (e.g., model.pkl)<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Dependencies list (requirements.txt)<\/span><\/li>\n<\/ul>\n<h3><span style=\"font-weight: 400;\">2. Set Up Your EC2 Instance<\/span><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sign into your AWS account<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Launch an EC2 instance using Ubuntu 20.04<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Select the appropriate <\/span><b>AWS ec2 instance types<\/b><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Add security group rules to allow HTTP (port 80) and SSH (port 22)<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Generate .pem key for SSH access<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">This setup gives you a virtual Linux server in the cloud.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">3. Access Your EC2 Server via SSH<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Use this command:<\/span><\/p>\n<p><i><span style=\"font-weight: 400;\">ssh -i &#8220;your-key.pem&#8221; ubuntu@&lt;ec2-ip-address&gt;<\/span><\/i><\/p>\n<h3><span style=\"font-weight: 400;\">4. Install Python and Dependencies<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Inside EC2, run:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">sudo apt update<\/span><\/p>\n<p><span style=\"font-weight: 400;\">sudo apt install python3-pip<\/span><\/p>\n<p><span style=\"font-weight: 400;\">pip install flask joblib scikit-learn<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Upload your model and script using <\/span><span style=\"font-weight: 400;\">scp<\/span><span style=\"font-weight: 400;\"> or GitHub. Create a Python file (<\/span><span style=\"font-weight: 400;\">app.py<\/span><span style=\"font-weight: 400;\">) to load the model and handle predictions.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">5. Build a Simple Flask API<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Here\u2019s a basic example:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">from flask import Flask, request, jsonify<\/span><\/p>\n<p><span style=\"font-weight: 400;\">import joblib<\/span><\/p>\n<p><span style=\"font-weight: 400;\">app = Flask(__name__)<\/span><\/p>\n<p><span style=\"font-weight: 400;\">model = joblib.load(&#8216;model.pkl&#8217;)<\/span><\/p>\n<p><span style=\"font-weight: 400;\">@app.route(&#8216;\/predict&#8217;, methods=[&#8216;POST&#8217;])<\/span><\/p>\n<p><span style=\"font-weight: 400;\">def predict():<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00a0\u00a0\u00a0\u00a0data = request.get_json(force=True)<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00a0\u00a0\u00a0\u00a0prediction = model.predict([data[&#8216;input&#8217;]])<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00a0\u00a0\u00a0\u00a0return jsonify(prediction.tolist())<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">6. Host Your Flask App with Gunicorn or Nginx<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">You can run the Flask server using:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">gunicorn &#8211;bind 0.0.0.0:80 app:app<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This lets you expose the API to external users.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">7. Test Your Model\u2019s Endpoint<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Use Postman or cURL to send test requests:<\/span><\/p>\n<p><span style=\"font-weight: 400;\">curl -X POST http:\/\/&lt;ec2-ip&gt;\/predict -H &#8220;Content-Type: application\/json&#8221; -d &#8216;{&#8220;input&#8221;: [5.1, 3.5, 1.4, 0.2]}&#8217;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">You should see your model\u2019s prediction in response.<\/span><\/p>\n<h4><i><span style=\"font-weight: 400;\">Master Real-World ML Skills with Imarticus Learning<\/span><\/i><\/h4>\n<p><span style=\"font-weight: 400;\">If you\u2019re looking to go beyond basic Python scripts and truly master machine learning model deployment, the <\/span><a href=\"https:\/\/imarticus.org\/pg-program-data-science-ai\/\"><span style=\"font-weight: 400;\">Executive Post Graduate Programme in Data Science and Artificial Intelligence<\/span><\/a><span style=\"font-weight: 400;\"> by Imarticus Learning is a strong place to start. This 11-month course, offered in association with AWS, helps professionals future-proof their careers with a curriculum infused with cutting-edge GenAI technologies.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Rather than focusing only on theory, this programme takes a <\/span><b>project-first approach<\/b><span style=\"font-weight: 400;\">. You\u2019ll begin by working on real-world business challenges and learn new tools and concepts just in time, exactly when you need them. With over 35 tools and projects included, the hands-on learning experience is one of the strongest features.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">What makes it even more valuable is the <\/span><b>global capstone project<\/b><span style=\"font-weight: 400;\">, where you\u2019ll solve a real business problem from an international startup. Completing this project earns you a capstone certificate, which adds credibility to your CV and LinkedIn profile.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">You\u2019ll also benefit from <\/span><b>dedicated career support<\/b><span style=\"font-weight: 400;\">. Imarticus Learning provides assistance with CV building, mock interviews, and exclusive job portal access to help you land the right role faster. Plus, the <\/span><b>AI and Cloud Conclave<\/b><span style=\"font-weight: 400;\"> gives you an opportunity to connect face-to-face with industry leaders and broaden your professional network.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Learning happens over the weekend through interactive online sessions, ideal if you\u2019re working full-time but still want to upskill with the latest advancements in AI, cloud, and machine learning deployment.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you\u2019re serious about deploying machine learning models on platforms like AWS EC2 and want career-ready skills, enrol in the <\/span><b>Executive Post Graduate Programme in Data Science and Artificial Intelligence<\/b><span style=\"font-weight: 400;\"> by Imarticus Learning. Build, test, and deploy with confidence to get ready for the future.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Enrol in the <\/span><b>Executive Post Graduate Programme in Data Science and Artificial Intelligence<\/b><span style=\"font-weight: 400;\"> today and start deploying your models like a pro.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">FAQ<\/span><\/h3>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>What is AWS EC2 used for in machine learning?<\/b><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">AWS EC2 provides scalable cloud computing power to run and deploy machine learning models efficiently.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>How to deploy machine learning models on AWS EC2?<\/b><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">Train your model, launch an EC2 instance, install dependencies, and host your model using a Flask API.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Which AWS EC2 instance types are good for ML?<\/b><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">GPU-based types like <\/span><span style=\"font-weight: 400;\">g4dn<\/span><span style=\"font-weight: 400;\"> or <\/span><span style=\"font-weight: 400;\">p3<\/span><span style=\"font-weight: 400;\"> are best for training; <\/span><span style=\"font-weight: 400;\">m5<\/span><span style=\"font-weight: 400;\"> or <\/span><span style=\"font-weight: 400;\">t2<\/span><span style=\"font-weight: 400;\"> work well for basic model deployment.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Can beginners use AWS for machine learning model deployment?<\/b><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">Yes, AWS offers a Free Tier with <\/span><span style=\"font-weight: 400;\">t2.micro<\/span><span style=\"font-weight: 400;\"> that\u2019s ideal for learning model deployment basics.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>What is the benefit of learning AWS EC2 for data science?<\/b><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">It teaches cloud deployment, a crucial skill for transitioning ML models into production.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Does the Programme in Data Science and Artificial Intelligence teach model deployment?<\/b><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">Yes, it includes hands-on projects using AWS and GenAI technologies for end-to-end learning.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>How long does it take to deploy a model on EC2?<\/b><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">With basic Python and cloud knowledge, a simple deployment can take under an hour.<\/span><\/li>\n<\/ol>\n<p><b>Is AWS EC2 secure for machine learning deployments?<\/b><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">Yes, with proper security groups and key management, EC2 provides a safe environment.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Are You Still Struggling to Launch Machine Learning Model Deployment Live? Ever trained a brilliant model but couldn\u2019t figure out how to get it into users\u2019 hands? You\u2019re not alone. Many data science learners and early professionals get stuck between \u201ctraining\u201d and \u201cdeployment.\u201d Knowing how to deploy machine learning models effectively is what turns your [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":268800,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_mo_disable_npp":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[22],"tags":[5259],"class_list":["post-268799","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-finance","tag-machine-learning-model-deployment"],"acf":[],"aioseo_notices":[],"modified_by":"Imarticus Learning","_links":{"self":[{"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/posts\/268799","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/comments?post=268799"}],"version-history":[{"count":1,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/posts\/268799\/revisions"}],"predecessor-version":[{"id":268801,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/posts\/268799\/revisions\/268801"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/media\/268800"}],"wp:attachment":[{"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/media?parent=268799"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/categories?post=268799"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/tags?post=268799"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}