Deep learning engineer
Starting at
$
200
/hrAbout this service
Summary
A range of services related to the development and implementation of deep learning models. Some of the key services provided here include:
Consultation: consultation services to help clients determine whether deep learning is the appropriate approach for solving a particular problem. I help clients understand the benefits and limitations of deep learning and identify the best deep learning models and frameworks to use for a specific application.
Model Development: I design and develop custom deep learning models in the area of natural language processing, recommendation, and computer vision. This includes selecting appropriate neural network architectures, defining the model's input and output layers, and choosing the best optimization and training strategies to achieve optimal performance.
Model Evaluation and Optimization: I evaluate the performance of existing deep learning models and optimize them to improve their accuracy and efficiency. This involves fine-tuning hyper-parameters, applying regularization techniques, and using advanced optimization methods to achieve better performance.
Model Deployment: I deploy deep learning models to production environments, ensuring that the models are scalable, reliable, and secure. I also monitor the models' performance and troubleshoot any issues that arise.
Research and Development: I can conduct research to advance the state-of-the-art in deep learning and contribute to the development of new deep learning algorithms, models, and frameworks.
Overall, I provide a range of valuable services to help clients solve complex problems using advanced machine learning and artificial intelligence techniques. I help clients leverage the power of deep learning to gain insights, make predictions, and automate tasks in a variety of industries and applications.
What's included
Deep learning model code
Deep learning model for specific problem including natural language, recommendation, computer vision, etc.
Trained model
Model parameters which was trained on GPU machines and validated on specified dataset.
Inference service
Micro-service of the deep learning model which is wrapped into docker containers and ready to be deployed into production.
Example projects
Skills and tools
Backend Engineer
ML Engineer
Python
PyTorch