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English
$
USD
I will develop ml and CNN models for classification and regression
AI Engineer, AI Agents, RAG Systems and ML Automations
Hi, I'm Moiz Ahmed Mansoori — an AI developer with 3+ years of building AI, ML, and Multi-Agent systems with 8+ real projects under my belt.
I build: AI Agents and chatbots (LangChain, LangGraph), ML ...
About this Gig
Are you looking for a custom machine learning or deep learning solution that delivers accurate results on your data?
I will develop ML and CNN models for classification and regression using Python, TensorFlow, Keras, XGBoost and scikit-learn.
WHY CHOOSE ME?
- Built AIRO, a 6-agent ML research orchestrator for automated experimentation
- Developed a Brain Tumor Detection system using VGG16 and Grad-CAM
- Experience with end-to-end ML pipelines, explainability, and deployment
WHAT YOU GET:
- Custom ML and deep learning models
- CNN models for image classification
- Data preprocessing and feature engineering
- Hyperparameter tuning and evaluation
- SHAP explainability and feature importance
- Clean, documented source code
- FastAPI or Streamlit deployment support
PERFECT FOR:
- Image classification and computer vision
- Business prediction and forecasting
- Medical imaging and research projects
- Regression on structured datasets
TECH STACK:
Python, TensorFlow, Keras, PyTorch, scikit-learn, XGBoost, SHAP, MLflow, FastAPI
Message me before ordering to discuss your dataset and requirements.
Programming language:
Python
Frameworks:
Scikit-learn
•
Keras
•
PyTorch
•
Panda
•
Other
APIs:
Other
Tools:
Jupyter Notebook
•
Colab
My Portfolio
FAQ
What data do you need to get started?
Share your dataset in CSV, Excel or image format along with your target variable and problem type. I will handle all preprocessing and cleaning.
Can you work with image datasets for CNN models?
Yes. I work with image classification, object detection and medical imaging datasets. I use TensorFlow, Keras and OpenCV for all CNN projects.
What evaluation metrics do you provide?
I provide accuracy, precision, recall, F1 score, ROC-AUC, confusion matrix and SHAP explainability plots — so you fully understand your model performance.
Will I receive the source code?
Yes. All packages include complete source code, a README with setup instructions and model evaluation report. Premium includes deployment guide.
Can you improve my existing model?
Yes. Share your current model and dataset. I will analyze performance bottlenecks, apply hyperparameter tuning, feature engineering and optimization to improve accuracy and generalization.
