For a given 2 folders with images of different size, make a simple to read deep learning model using tensorflow or pytorch to classify images into one of those two classes.
The task should be done using jupiter notebok
Data can be found at [login to view URL]
The solution should work even if file names are replaced and more files added.
The solution should use of at least one convolutional layer.
Remember this is a very short project, and it should be a short programming code and easy to read.
Hi. My name is Uzair.I did my masters in Electrical Engineering. I have done my thesis in biomedical signal processing and Machine learning.
I have more than 3 years of experience in Python/MATLAB specially in Machine learning, Image processing and Signal processing.
I have knowledge and understanding of state of the art machine learning algorithms like SVM, neaural networks as well as basic algos like KNN and clustering. I have also worked with sklearn and keras in PYTHON.
I have recently organized a bootcamp on AI and machine learning in my university.
Due to my vast coding experience , I can handle your project with quality work. Kindly share some more details so that I can offer the exact solution to your problem.
Regards
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Hello sir
I am a qualified python developer with rich experiences of machine learning. I have made many models with cnn algorithms. I got your idea and am ready to start the work.
Looking forward to hearing from you soon.
Best Regards,
Yongtao
Hello sir,
We are interested in your project. This week we implemented similar project of image classification using both CNN and RNN. Please check our profile.
We used Jupiter Notebook, tensorflow and there was convolution layer.
We have one question. Do you want us to use Keras? May we know your python version?
Sincerely
Nazmul