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English
$
USD
I will do deep learning models using pytorch and tensorflow
Level 1
Has met certain performance criteria and shows strong potential in the marketplace.
About this Gig
Looking for custom deep learning solutions? I specialize in developing powerful models using PyTorch and TensorFlow for various applications, including computer vision, natural language processing (NLP), time series forecasting, and more.
I can help you with:
- Custom Model Development: Tailored models designed for your specific project needs.
- Transfer Learning: Leveraging pre-trained models to boost performance with less data.
- Optimization: Fast, efficient models optimized for production deployment.
- Deployment: I offer end-to-end solutions, from training models to deploying them on cloud platforms.
Why Choose Me?
- Experienced: I have in-depth knowledge of PyTorch and TensorFlow and can handle both simple and complex models.
- Efficient: I ensure optimized models that balance speed and accuracy.
- Clean Code: You'll receive organized, well-documented code, making it easy to scale or modify as needed.
- End-to-End Solutions: From data preprocessing, training, and model evaluation to deployment and support, I handle the full pipeline.
What I need: Your project details, dataset, and any specific requirements. Contact me today to get started!
Programming language:
Python
•
Java
APIs:
Google Cloud Vision API
•
Azure Face API
Tools:
Jupyter Notebook
•
OpenCV
•
TensorFlow
•
MLflow
•
SimpleCV
Frameworks:
Scikit-learn
•
DeepPy
•
SimpleCV
•
Keras
•
PyTorch
•
TensorFlow
FAQ
How long does it take to develop a model?
The timeline depends on the complexity of the project. Simple models can take a few days, while more advanced ones might take a couple of weeks. I will provide you with an estimated timeline during our initial consultation.
What type of data do I need to get started?
For image-related tasks, you’ll need labeled images; for NLP, text data; for time series, a sequence of time-based data. More data generally results in better performance, but we can also work with limited data through transfer learning techniques.
