You will get your machine learning model deployed on AWS as a live, scalable REST API
Project details
I'll take your machine learning model out of the notebook and put it into production on AWS: a live, scalable, monitored API endpoint your app can actually call, with retraining set up so accuracy doesn't quietly decay.
WHAT YOU GET
✔ Model containerised with Docker and deployed to AWS
✔ Live REST API endpoint (SageMaker, Lambda or ECS, whichever fits your load)
✔ Autoscaling and load handling configured for your traffic
✔ CI/CD pipeline via GitHub Actions so updates ship safely
✔ Data-drift and performance monitoring with alerts
✔ IAM least-privilege setup, cost estimate and a full runbook
ALSO COVERS
S3 data lakes, Glue ETL jobs, Athena querying, Lambda triggers, CloudWatch dashboards and scheduled retraining.
PROCESS
1. Share your model / notebook and expected request volume
2. I containerise, deploy and load-test it
3. Hand over with docs, monitoring and a cost breakdown
WHY ME
Top 10% on Upwork. 100+ projects delivered. Under 1 hour response time. Production-ready, not demo-ready.
Message me your model and traffic expectations first.
WHAT YOU GET
✔ Model containerised with Docker and deployed to AWS
✔ Live REST API endpoint (SageMaker, Lambda or ECS, whichever fits your load)
✔ Autoscaling and load handling configured for your traffic
✔ CI/CD pipeline via GitHub Actions so updates ship safely
✔ Data-drift and performance monitoring with alerts
✔ IAM least-privilege setup, cost estimate and a full runbook
ALSO COVERS
S3 data lakes, Glue ETL jobs, Athena querying, Lambda triggers, CloudWatch dashboards and scheduled retraining.
PROCESS
1. Share your model / notebook and expected request volume
2. I containerise, deploy and load-test it
3. Hand over with docs, monitoring and a cost breakdown
WHY ME
Top 10% on Upwork. 100+ projects delivered. Under 1 hour response time. Production-ready, not demo-ready.
Message me your model and traffic expectations first.
Machine Learning Tools
Python, TensorFlowWhat's included
| Service Tiers |
Starter
$60
|
Standard
$90
|
Advanced
$150
|
|---|---|---|---|
| Delivery Time | 3 days | 6 days | 8 days |
Number of Revisions | 2 | 3 | 5 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$10Frequently asked questions
About Muhammad Fasih
DataScience|Data Analysis|Machine Learning|Data Visualization|Python|R
Islamabad, Pakistan - 9:40 am local time
🎖️ 2+ Years of Experience | 100+ Projects Delivered
⏱️ Under 1 Hour Response Time | Cross-Industry Expertise
🌐 Supporting Startups, Enterprises & Tech Teams Worldwide
🚀 Unlock the Power of Data with Expert AI & Data Solutions
I help businesses build AI-powered products, automate workflows, and extract actionable insights. With hands-on experience in machine learning, cloud deployment, and analytics, I deliver scalable, production-ready solutions tailored to your goals.
🎯 Looking to develop smart AI systems, automate decision-making, or launch powerful dashboards? Let’s get started.
💡 Core Expertise Areas
🔹 Generative AI and LLM Applications (GPT, RAG, Fine-tuning)
🔹 Predictive Modeling and Business Intelligence
🔹 Deep Learning (Computer Vision, NLP, Transformers)
🔹 Custom AI Chatbots and Natural Language Understanding
🔹 ML Ops, Cloud Deployment, and CI/CD Automation
🔹 Advanced Data Pipelines and Data Warehousing
🔹 Real-time KPI Dashboards and Performance Tracking
🛠️ Skills I Possess
💻 Programming & Libraries
👉 Python (NumPy, Pandas, Scikit-learn, Polars, TensorFlow, Keras)
👉 R
👉 SQL (PostgreSQL, MySQL, SQLite)
📊 Machine Learning Techniques & Statistics
👉 Regression, Gradient Boosting, Maximum Likelihood Estimation
👉 Probabilistic Graphical Models, Deep Learning
👉 Hyperparameter Tuning, Feature Engineering
⚙️ Data Processing & Engineering
👉 Apache Spark, Python Polars, AWS Glue
👉 Apache Airflow, dbt, Mage
📈 Visualization & Dashboards
👉 Tableau, Looker Studio, Power BI, Seaborn, Plotly
☁️ Cloud & Infrastructure
👉 AWS (S3, Lambda, SageMaker, Athena)
👉 GCP (BigQuery, Vertex AI)
👉 Docker, Streamlit, CI/CD
📦 Databases & Storage
👉 PostgreSQL, MySQL, SQLite
👉 AWS Athena, GCP BigQuery
👉 Data Lakes and Warehouse Architecture
💼 Services I Offer
🤖 ML/AI Product Development
👉 Transform your ML vision into a clear product plan with a defined roadmap and timeline.
🧪 Machine Learning & Data Software Engineering
👉 I can start from scratch or quickly integrate into your existing project. I specialize in optimization, scalability, and fast delivery within 24 hours.
☁️ Cloud Development
👉 Deploy, monitor, and optimize ML or data pipelines in AWS or GCP environments.
📊 Business Intelligence & Automation
👉 Build intelligent dashboards and automate your business processes to unlock time and efficiency.
📈 Technical Stack Summary
🧠 Languages: Python, R, SQL
🧠 Libraries: Scikit-learn, TensorFlow, PyTorch, Pandas, Polars, Hugging Face
🧠 Visualization Tools: Looker Studio, Tableau, Power BI, Seaborn, Plotly
🧠 Cloud Platforms: AWS, GCP
🧠 Deployment: Docker, Streamlit, CI/CD
🧠 Workflow Tools: Apache Airflow, Mage, dbt
🧠 Databases: BigQuery, Athena, PostgreSQL, MySQL
🌟 Why Clients Choose Me
✅ Scalable and Production-Ready Solutions
✅ Business-Aligned AI and Data Strategies
✅ Fast Onboarding with Clear Communication
✅ Thorough Documentation and Smooth Handoff
✅ SEO-Friendly, High-Performance Deliverables
✅ Agile Collaboration and Frequent Progress Updates
🎯 Ideal If You Need
🔍 Generative AI or Custom LLM Integration
🔍 Full-Stack Machine Learning Solutions
🔍 Real-Time KPI Dashboards
🔍 Predictive Analytics or Time Series Forecasting
🔍 Chatbots and NLP-Driven Tools
🔍 Automated Business Workflows
🔍 Deep Learning in Vision or Language
🔍 Data Pipelines using dbt, Airflow, Glue
🔍 Cloud-Based Deployment and MLOps
📨 Ready to turn your data into intelligence and automation? Message me today and let’s build something impactful together.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Fasih can start the project.
Delivery time starts when Muhammad Fasih receives requirements from you.
Muhammad Fasih works on your project following the steps below.
Revisions may occur after the delivery date.
Model review & architecture plan
I review your model and traffic expectations, then recommend the AWS architecture and give you a monthly cost estimate before any infrastructure is created. No surprise bills.
Containerisation & deployment
I containerise the model with Docker and deploy it to a live endpoint in your AWS account, with IAM permissions scoped to only what the service actually needs to run.