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I will build production ready machine learning pipelines in python
Nivel 2
Ha cumplido con los criterios de alto rendimiento y tiene un historial comprobado de cumplimiento de las expectativas de los clientes.
Acerca de este Servicio
I can develop an end-to-end ML/DL solution, from data preparation and model training to evaluation, optimization, API integration and production deployment.
WHAT I CAN BUILD
Machine Learning
- Classification
- Regression
- Clustering
- Anomaly detection
- Recommendation systems
- Predictive modeling
- Feature engineering
- Model evaluation and comparison
Deep Learning
- Neural network development
- Transfer learning
- CNN-based models
- Custom deep learning architectures
- Model fine-tuning
- Training and validation pipelines
- Hyperparameter optimization
Computer Vision
- Image classification
- Object detection
- Image segmentation
- Object tracking
- Image similarity
- OCR pipelines
- Visual inspection systems
- Custom image analysis solutions
END-TO-END ML PIPELINE
I can develop the complete workflow:
Data Preprocessing > Training > Evaluation > Optimization > Inference >API > Deployment
This include:
- Dataset preparation
- Data preprocessing and augmentation
- Train/validation/test pipelines
- Model training
- Experiment tracking
- Performance evaluation
- Error analysis
- Model optimization
- Inference pipeline
- REST API
- Docker containerization
- Deployment assistance
Please contact me before ordering so I can review your requirements.
Mi porfolio
Otros servicios de Ciencia de datos y aprendizaje automático que ofrezco
FAQ
Can you train a model using my dataset?
Yes. I can develop the preprocessing, training, validation and evaluation workflow around your dataset.
Can you work with an existing model?
Yes. I can fine-tune, optimize, modify, evaluate, or deploy an existing ML/DL model depending on the project.
Can you build computer vision models?
Yes. I can work on tasks including image classification, object detection, segmentation, OCR, tracking and other image-based ML problems.
Can you deploy my trained model?
Yes. I can create an inference pipeline and, depending on the package, expose the model through an API, Docker container, or deployment environment.
Can you create a complete ML pipeline?
Yes. A complete pipeline can include preprocessing, training, validation, evaluation, inference, API integration, containerization and deployment.
Can you optimize model inference?
Yes. Depending on the model and target hardware, optimization can include preprocessing improvements, batching, model conversion, quantization, or other inference optimizations.
Do you provide the trained model and source code?
Yes. The applicable package includes the relevant source code and trained model artifacts where technically and legally possible.
