machine learning for image classification project
Budget: $250 – $750 USD
There are approximately 1700 “X” pictures and 700 “Y” pictures.
The goal is to enter a new picture to the computer, in Python and he will be able to tell us if it is a “X” or “Y” pictures. The desired rate of success for identification is above 95%.
The Python program should support both MAC M1 (support for its neural engine) and windows PC.
I know I don’t have enough “Y” pictures, but for the sake of work you can train 1500 “X” pics and 500 “Y” pics and then input the remaining 200 of each to the neural network, to test the results (How it handles new pictures)
There is a must to use Python language, with known and trusted frameworks: TensorFlow, Pytorch, Keras, Numpy etc.
At the end I will get the code, and FULL explanation how the model was trained, how to improve it, the tools that were used and the results.
The goal is to enter a new picture to the computer, in Python and he will be able to tell us if it is a “X” or “Y” pictures. The desired rate of success for identification is above 95%.
The Python program should support both MAC M1 (support for its neural engine) and windows PC.
I know I don’t have enough “Y” pictures, but for the sake of work you can train 1500 “X” pics and 500 “Y” pics and then input the remaining 200 of each to the neural network, to test the results (How it handles new pictures)
There is a must to use Python language, with known and trusted frameworks: TensorFlow, Pytorch, Keras, Numpy etc.
At the end I will get the code, and FULL explanation how the model was trained, how to improve it, the tools that were used and the results.
Related categories:
Python
Software Architecture
Machine Learning (ML)
Image Processing
Deep Learning