Need to Fine tune model to avoid const val accuracy ,val precision,val recall

Cerrado Publicado hace 2 años Pagado a la entrega
Cerrado Pagado a la entrega

I have dataset of retina disease , which is basically a mullticlass dataset I want someone to fine tune model to resolve the const val parameter issue, and accuracy should be at least 90%.

link for dataset - [login to view URL]

link for notebooks - [login to view URL]

Machine Learning (ML) Deep Learning Computer Vision

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10 propuestas Proyecto remoto Activo hace 2 años

10 freelancers están ofertando un promedio de ₹10667 por este trabajo

pandaPython123

Hi, I am doing my PhD in computer vision and deep learning. I have 4 years experience in tensorflow and keras. I would be happy to help you with your project. Best, Mehdi

₹12000 INR en 7 días
(9 comentarios)
4.8
FirmMinds123

We have AI & Data Science team who are highly experienced in Machine learning and Deep Learning and can deliver products as per your requirements. We have done many real time projects like Semantic search engine, Image Más

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(23 comentarios)
4.9
suyashdhoot

Hi I am a very experienced biostatistician, data scientist and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several c Más

₹30000 INR en 7 días
(21 comentarios)
5.4
kishan99999

Hi, Straight to the point, I am quite familiar with multiclass semantic segmentation that you are looking for the retina disease problem. I can train the model with high accuracy using python notebook on tesla GPU. M Más

₹10000 INR en 9 días
(0 comentarios)
3.2
Raja08021991

I am good in machine learning algorithms in terms of classification and regression. I have also expert in python coding. ping me if you need my assistance.

₹10000 INR en 3 días
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0.0
AkashRawatML

This is my area of expertise. I have been doing predictive modelling from last three years and moerover I had recently delivered such projects with above 90% accuracies.

₹7000 INR en 5 días
(0 comentarios)
0.0