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You will get a model which can predict wheat yield using Machine Learning

Muhammad T.Status: Offline
Muhammad T.
Preview image

Let a pro handle the details

Buy Machine Learning services from Muhammad, priced and ready to go.
Muhammad T.Status: Offline
Muhammad T.
Preview image

Let a pro handle the details

Buy Machine Learning services from Muhammad, priced and ready to go.

Project details

You will get a complete and fully functional Machine Learning Model for the prediction of Wheat Yield. This model keeps in mind all the constraints and environmental variables when creating this Model.
Machine Learning Tools
ChatGPT, Google Data Studio, Microsoft Excel, NumPy, pandas, Python, Python Scikit-Learn

What's included $1,500

These options are included with the project scope.

$1,500
  • Delivery Time 3 days
  • Number of Revisions 2
  • Number of Model Variations 2
  • Number of Scenarios 5
  • Number of Graphs/Charts 15
    • Model Documentation
    • Source Code
Muhammad T.Status: Offline

About Muhammad

Muhammad T.Status: Offline
AI Engineer | LLM Fine-tuning, RAG, Multi-Agent Systems
Islamabad, Pakistan - 4:52 pm local time
AI Engineer specializing in LLM fine-tuning, RAG, and multi-agent systems. Currently shipping production ML at Cointegration, where I built multi-agent workflows with LangChain and AutoGen that cut data retrieval latency by 40%, plus automated reasoning pipelines using Model Context Protocol that replaced 15 hours per week of manual processing. Recent work: Qwen 2.5 7B QLoRA fine-tune on Urdu where v2 hit 66% win rate vs. base across an 8-task evaluation harness. The most useful finding was an 18-point disagreement between Claude, Gemini, and GPT-5 as judges on the same eval, so I treat single-judge evaluation as a smoke test now and use multi-judge medians for final reporting. I work best on:

LLM fine-tuning with QLoRA, including eval design and catastrophic forgetting diagnosis
RAG pipelines and vector search
Multi-agent systems with LangChain, AutoGen, CrewAI, and Model Context Protocol
MLOps pipelines with model gating and SHAP explainability
Stack: Python, PyTorch, LangChain, AutoGen, CrewAI, OpenAI SDK, MCP, Docker, FastAPI, PostgreSQL, scikit-learn, SHAP.I'm doing my Master's in AI Engineering and available 20+ hours per week. PKT timezone (UTC+5), full overlap with EU clients and morning overlap with US East Coast.

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.

Do a complete background research of the area thoroughly.

Review the work, release payment, and leave feedback to Muhammad.