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$
USD
I will build ml and deep learning models in python
AI Engineer, Computer Vision , Deep Learning , Python and YOLO Expert
Looking for an AI engineer who builds production-ready systems, not just theoretical models?
I’m Hussnain (BS AI, Islamia University of Bahawalpur), specializing in end-to-end AI deployment:
• Compute...
About this Gig
Looking for high-performance Machine Learning or Deep Learning solutions tailored to your real-world data?
I build and deploy custom AI models using Python, PyTorch, TensorFlow, and Scikit-Learn. From complex computer vision pipelines to structured predictive analytics, I deliver clean, modular code engineered for accuracy and generalization.
Expertise & Capabilities:
- Deep Learning: CNNs, LSTMs, Transformers, and custom neural architectures.
- Computer Vision: Real-time object detection (YOLO), segmentation, MTCNN face recognition, video analytics.
- Machine Learning: XGBoost, Random Forest, classification, regression, clustering, anomaly detection.
- Data Engineering: Data cleaning, EDA, feature extraction, augmentation, handling imbalanced classes.
- Production Deployment: REST APIs (FastAPI/Flask), Streamlit dashboards, Docker containers
Development Workflow:
- Exploratory Data Analysis & Preprocessing
- Architecture Selection & Benchmark Training
- Hyperparameter Tuning & Cross-Validation
- Evaluation (Confusion Matrix, ROC-AUC, F1-Score)
- Exporting weights, source code, and deployment setup
Programming language:
Python
•
SQL
•
Colab
•
MLflow
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Amazon SageMaker
Frameworks:
Scikit-learn
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Google ML Kit
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Keras
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PyTorch
•
Panda
My Portfolio
Other Data Science & ML Services I Offer
FAQ
Can you train and evaluate a model using my custom dataset?
Yes. I work with custom tabular data (CSV/Excel/SQL), image folders, or video feeds. My workflow includes exploratory data analysis (EDA), cleaning, handling class imbalances, data augmentation, and structured feature engineering to prepare your dataset for optimal training.
What frameworks, libraries, and tools do you use?
I primarily develop in Python using PyTorch, TensorFlow, Keras, Scikit-Learn, OpenCV, and Pandas. Deliverables can be provided in Jupyter Notebook, Google Colab, or modular, production-ready Python files (.py) depending on your requirements.
Do you handle both classical Machine Learning and Deep Learning?
Yes. For structured/tabular data, I build models using algorithms like Random Forest, XGBoost, and LightGBM. For complex, unstructured data, I design deep neural networks, including CNNs, LSTMs, and modern vision or sequence architectures.
Can you develop Computer Vision and real-time detection systems?
Yes. I specialize in computer vision tasks such as real-time object detection (YOLO), facial detection/recognition, tracking, and image segmentation. I can process both static image datasets and live video streams using OpenCV.
How do you validate model performance and prevent overfitting?
I use rigorous evaluation techniques including train-validation-test splitting, cross-validation, and metric tracking. You will receive clear validation reports featuring metrics such as Confusion Matrices, Precision-Recall curves, F1-Scores, ROC-AUC, or loss/accuracy plots.
What file formats and deliverables will I receive?
You receive full ownership of the clean, well-commented source code alongside the trained model weights/checkpoints in standard formats (such as .pt, .pth, .h5, .onnx, or .pkl) with a step-by-step setup guide.
Can you deploy the model or provide an API/UI?
Yes. Under the Premium tier (or as an add-on), I can package your trained model into a REST API (FastAPI/Flask), build an interactive prototype dashboard using Streamlit, or configure a Dockerfile for seamless cloud deployment on AWS, Azure, or GCP.
