You will get Custom Machine Learning Model Development & Deployment
Top Rated
Top Rated
Project details
I design and build custom machine learning models tailored to your business problem, covering the full ML lifecycle from data preprocessing to deployment.
This includes supervised and unsupervised learning, predictive analytics, classification, regression, and recommendation systems. Models are trained, evaluated, optimized, and deployed as scalable APIs.
What you get:
Data preprocessing & feature engineering
Model training & evaluation
Hyperparameter tuning & optimization
API deployment (FastAPI, Docker)
Cloud-ready ML systems (AWS / GCP)
Focused on accuracy, scalability, and real-world performance.
This includes supervised and unsupervised learning, predictive analytics, classification, regression, and recommendation systems. Models are trained, evaluated, optimized, and deployed as scalable APIs.
What you get:
Data preprocessing & feature engineering
Model training & evaluation
Hyperparameter tuning & optimization
API deployment (FastAPI, Docker)
Cloud-ready ML systems (AWS / GCP)
Focused on accuracy, scalability, and real-world performance.
Machine Learning Tools
Azure Machine Learning, ChatGPT, Google AutoML, Google Data Studio, GPT-3, Keras, MATLAB, Minitab, NumPy, Open Neural Network Exchange, OpenCV, pandas, PyMC, Python, Python Scikit-Learn, PyTorch, scikit-learn, TensorFlow, Tesseract OCRWhat's included
| Service Tiers |
Starter
$200
|
Standard
$500
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 4 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 2 | 5 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - | - |
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About Muhammad
AI Agent Developer | Automation & n8n Workflows | Python Expert
100%
Job Success
Columbus, United States - 7:28 pm local time
With 7+ years in AI, machine learning, and backend engineering, I combine hands-on LLM and agent development with clean, production-grade Python architecture. Most freelancers stop at a prototype; I deliver systems that run reliably at scale using FastAPI, Flask, and Django.
Here is how I can help your business:
🤖 AI Agents & LLM Apps: I build AI agents, multi-agent systems, and assistants using OpenAI, Claude, Gemini, and LLaMA, including RAG pipelines with Pinecone, Weaviate, and ChromaDB for enterprise knowledge bases.
⚙️ Automation & Integrations: I connect AI models to your real business systems using n8n, Zapier, and Make, automating CRM workflows, Stripe/PayPal processes, and internal operations to reduce manual effort.
📊 Machine Learning & Computer Vision: I build predictive models, recommendation systems, OCR pipelines, and document AI using TensorFlow, PyTorch, and OpenCV.
🛠️ Backend & API Engineering: I design scalable AI APIs and cloud-ready backend systems using FastAPI, Flask, Django, REST, and GraphQL, handling the full lifecycle from data processing to deployment.
Results I have delivered:
✅ Built a recommendation engine that increased client conversions by 30%
✅ Developed an AI chatbot that reduced customer response time by 70%
✅ Created OCR and document AI pipelines cutting manual processing by 50%
✅ Built AI automation systems reducing operational effort by 60%
✅ Delivered a load optimization MVP for a freight routing platform ($4,000 fixed project)
Certified in Generative AI with Large Language Models (DeepLearning.AI / AWS) and Machine Learning Specialization (Stanford / Coursera). Rated 5.0 on Upwork with Top Rated status.
If you're building an AI agent, automation workflow, or need production-ready AI integration, send me a message and I'll respond within a few hours to discuss your project.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Understand Data & Problem Scope
Review dataset, clarify objectives, and define the modeling approach and evaluation metrics.
Data Preparation & Feature Engineering
Clean, preprocess, and engineer features to ensure model readiness and performance.