Machine Learning expert to implement simple ridesharing code (Python) – 3 days

I am looking for a Machine Learning/DQN expert with experience in Python to implement a simple ridesharing code. The project has a duration of 3 days. Preferred Skills and Experience: - Expertise in Python programming language - Strong knowledge of Machine Learning and Deep Q-Networks (DQN) - Experience in implementing advanced ridesharing algorithms Project Requirements: 1. A lot of the work has been done in this Github repo: [login to view URL] 2. Implement the repo ensuring multiple passengers can use a single vehicle when it’s efficient to do so. Make changes only when very necessary, but focus on delivering a clear, usable output. 3. The project is about ridesharing (multiple passengers using single vehicle when feasible), not about the repo….the repo is just to help you so you don’t have to write all the code from scratch 4. Make sure your code generates an easily understandable *output* eg showing vehicle 1 picks up passenger 1, then picks up passenger 2, then drops of passenger 2 and finally passenger 1. 5. Since most (but not all) of the work has been done in the repo, the deadline for this is in 3 days (starting today, 24/10/2023 at about 12pm UK time, and ending 12pm UK time on 27/10/2023). 6. Do some training, generate a model, save the model and demonstrate it can take a simple input trips request file and produce a trips plan output. 7. See attached “[login to view URL]” for options of output format (output should be in CSV or Excel). Let me know if you want to use any other format, but will most likely be ok if it's easily understandable. Coding for logging has been done in the repo. See section that states "5. The user can also choose to log the events associated with vehicles or not using". 8. Ensure your code produces reports (the code to do this is already part of the Github repo. see the section that says "Summary of Metrics for the simulation duration" in [login to view URL])