You will get your machine learning model deployed as an API or web app
Project details
You will get a professional machine learning deployment solution that transforms your trained ML model into a production-ready API or web application. Whether you need a FastAPI endpoint, Flask API, Streamlit dashboard, or cloud deployment solution, I build scalable ML systems that make your models accessible, interactive, and ready for real-world use.
This project can include ML API development, Streamlit web apps, model integration, prediction interfaces, deployment pipelines, cloud hosting support, and deployment-ready documentation tailored to your project requirements. Depending on your use case, deployment frameworks such as FastAPI, Flask, Streamlit, Docker, Render, Railway, and Python-based backend systems can be implemented for scalable machine learning applications.
Using tools like Python, FastAPI, Flask, Streamlit, Scikit-learn, Docker, and cloud deployment platforms, I focus on building reliable ML deployment solutions that help businesses move beyond notebooks into real production environments and user-ready AI applications.
This project can include ML API development, Streamlit web apps, model integration, prediction interfaces, deployment pipelines, cloud hosting support, and deployment-ready documentation tailored to your project requirements. Depending on your use case, deployment frameworks such as FastAPI, Flask, Streamlit, Docker, Render, Railway, and Python-based backend systems can be implemented for scalable machine learning applications.
Using tools like Python, FastAPI, Flask, Streamlit, Scikit-learn, Docker, and cloud deployment platforms, I focus on building reliable ML deployment solutions that help businesses move beyond notebooks into real production environments and user-ready AI applications.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
Azure Machine Learning, Deeplearning4j, Keras, MLflow, NVIDIA AI Platform, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$80
|
Standard
$200
|
Advanced
$400
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 6 days |
Number of Revisions | 1 | 2 | 4 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | ||
Model Documentation | - | - | |
Ontology | - | - | |
Source Code | - | - | |
Taxonomy | - | - |
Frequently asked questions
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AU
Akintobi U.
Jun 1, 2026
Excel Dashboard for Business Reporting
Azeez demonstrated outstanding attention to detail and business understanding throughout the project. His expertise in data analytics, reporting, and KPI tracking, leveraging Microsoft Excel, added significant value to our decision-making process.
LW
Li W.
Sep 15, 2023
Freelance HR Business Partner (1A35)
LW
Li W.
Aug 16, 2023
Freelance HR Business Partner (1A35)
NZ
Nan Z.
Jul 6, 2023
Recruiting Tasks (NncL): Resume Screening & Assessment
Olasupo helped us evaluate candidates for an open position in finance relating to our investments in technology, healthcare, publishing, philanthropy, and sustainability (ESG). Olasupo helped us in a timely and productive way, and was completely responsive and communicative about all our goals. We're thankful for the help and would consider working together again the next time we need an HR partner.
IE
Iyanulowa E.
Oct 26, 2022
Wix, Zapier and Activecampaign Expert
Thank you for your support and great communication. You clearly solvedmy integration problems... I'll definitely,, use your service again. Thanks.
About Olasupo
Inventory Planning | Demand Forecasting | Supply Chain Analytics
Ikeja, Nigeria - 1:19 pm local time
With a background in Industrial and Production Engineering and hands-on experience in supply chain operations, analytics, and business intelligence, I specialize in demand forecasting, inventory optimization, procurement analytics, KPI reporting, and supply chain performance analysis
I worked with an energy company in the gas-to-power sector where I applied data analytics and data science techniques to support operational efficiency and business decision-making by:
• Automating reporting pipelines and operational data workflows
• Cleaning, transforming, and analyzing large operational and energy datasets
• Building analytical dashboards for KPI monitoring and performance insights
• Supporting predictive and data-driven operational decision-making processes
• Improving data visibility, reporting efficiency, and business intelligence across operations
My technical toolkit includes:
• Excel & Google Sheets
• SQL (PostgreSQL, MySQL, SQL Server, SQLite)
• Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn)
• Time Series Forecasting (ARIMA, SARIMA, ARMA, VAR, VARMA, Holt-Winters, Prophet)
• Machine Learning & Predictive Analytics
• ML Model Deployment & Automation
• Tableau & Power BI
• Streamlit Dashboard Development
• Inventory Optimization & Supply Chain Analytics
• Data Cleaning, ETL & Business Reporting
I can help you with:
✔ Business dashboards & KPI reporting
✔ Demand forecasting & time series analysis
✔ Machine learning & predictive modeling
✔ Inventory and sales analytics
✔ Data cleaning, preprocessing & transformation
✔ Excel automation & reporting systems
✔ SQL queries, database analysis & ETL workflows
✔ ML deployment using Streamlit and Python apps
✔ Supply chain and operations analytics projects
I focus on delivering clean, scalable, and business-focused analytical solutions that help clients improve decision-making, optimize operations, reduce inefficiencies, and uncover meaningful insights from their data.
Let’s work together to turn your data into smart business solutions.
Steps for completing your project
After purchasing the project, send requirements so Olasupo can start the project.
Delivery time starts when Olasupo receives requirements from you.
Olasupo works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering
Client shares trained model, project goals, deployment requirements, and preferred platform.
Environment & API Setup
The deployment architecture, backend environment, and API structure are configured.