Implement a machine learning paper:
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
( [login to view URL] )
There is a Github repo implementing the project ([login to view URL] ).
The writer used Pytorch to implement the net.
I’ve started making his code work on my machine but I don’t have the time to complete it.
I’m using a Google Cloud ubuntu instance with an anaconda virtual environment.
I need someone to finish the setup for me.
The job will include a half-hour session ( e.g. skype) in which I will explain what I’ve done already.
The work will be made on my instance, credentials and any resources needed will be supplied by me.
The deliverable must include the following:
1. A working code that runs without errors and trains a machine to achieve results close to the results shown in the paper.
2. Documentation (could be partly inside of the code) regarding changes made to the original repo code for it to work
3. Detailed instructions regarding proper operation of the code - what I need to know to re-train the machine and to run the trained machine on test images