# Guidelines for selecting proposals
* General idea -> Give a brief idea of what you understood after reading the proposal.
* Innovation -> Level of innovation of the project.
* Relevance -> Your views on relevance with AI.
* Workable -> Your opinion of whether the project is workable or not
* Clarity -> Does the maker have enough clarity regarding the proposal and its execution ?
* Uniqueness -> Can the idea be found with a simple google search?
* Comments -> Your comments

* Read the guidelines thoroughly.

### Guidelines for first yearites:
* We don't expect the idea to be novel but it should not be a simple google search. The bare minimum, which should be rejected, is applying linear regression or logistic regression on a widely available dataset but any build up on this one like after making such a model they are trying to deploy it should be accepted.
* Debatable point, a project that can be found easily via google but is not as basic as the above mentioned project, should be accepted or not ? IMO we should consider this on the basis of finally selected proposals.
* If the project is workable by changing some part then its fine. Some of the proposals will give ideas on which no datasets might be available but model can be made, we should consider their ideas also, we can help them to build the model and later manually make a very small dataset just to check whether its working or not.
* Should clarity be given much weightage ? IMO as clarity of what they want to do should be important if their project is one of those simple google search as it will show that the person has tried to learn more about what they are doing. For other cases it should not be that much important.
* Filter out the proposal into two categories sure rejections and maybe.
* Be sure to mention the answer to the points mentioned at the start and any other short comments you feel necessary to justify your judgement, to make further shortlisting easier afterwards.

### Guidelines for second yearites:
* A research paper implementation or a well applied project having an innovative tinge in it.
* If the project is about an already implemented idea, it won’t be considered; unless their proposal talks about some new innovative element as their selling point (related to ML/DL).
* Proposals with vague mid-term end-term goals not to be accepted except in rare cases.
* Projects with far fetched ideas and lack of required corresponding research and details in proposal to be discarded
* Basically sample prposal should be strictly followed and details should be clear.

### Important Questions:
* How many to be shortlisted ?
* Mentorship ?
* After shortlisting ?

### MID EVALUATION and END EVALUATION ?