Budget: 200 EUR Deadline: 5 days
Hello, I am engaged in training neural networks and can help you with your issue) About myself, I am a computer vision developer with 4+ years of experience.
There is a dataset of 27 classes.
The distribution is not uniform - that is, consultation will be needed to improve the dataset and possible augmentation.
Task:
Compose a Python script for training a neural network for classification using YOLO and Faster R-CNN on our dataset including:

Also, a script that will load the model and use it (i.e., pass input data to the model - that is, several images and expect a response in the form of JSON with classes and % accuracy)
Budget: 200 EUR Deadline: 5 days
Hello, I am engaged in training neural networks and can help you with your issue) About myself, I am a computer vision developer with 4+ years of experience.
Budget: 250 EUR Deadline: 3 days
Hello
I am a Python developer
I have completed many similar projects
I am ready to take on the work and complete it in the shortest time in the best possible way
I perform the work efficiently and on time
You can read the reviews
Budget: 120 EUR Deadline: 1 day
Good day! I have experience = I can help with training the neural network!!! Feel free to reach out!
Budget: 200 EUR Deadline: 5 days
Good day. I am dealing with computer vision issues. The task does not seem complicated. I am ready to take on the execution. Plus, I can suggest a few other architectures that have shown better results than YOLO.
Budget: 200 EUR Deadline: 4 days
Good day
The task looks interesting and quite complex. There are several approaches to its implementation, so it is worth discussing the details for proper planning. The main logic is to set up a script for training the neural network on your dataset, taking into account the specifics of the data and the desired metrics. In the process, we will be able to:
Implement the necessary parameters for configuration (for example, batch size, learning rate, etc.).
Use appropriate augmentation to balance classes that have fewer examples.
Provide output of key metrics and graphs to track results during training, to have a complete understanding of the dynamics of the process.
After the first stage of configuration, we will be able to test the model and discuss the next steps to achieve optimal results.
I am ready to discuss the details to find the best solution and agree on how the results will look, including the JSON format for responses.
I look forward to your feedback to discuss all the details and the optimal approach to implementation.
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