github: issue templates: GSoC project idea

Author: pdxjohnny

.github/ISSUE_TEMPLATE/gsoc_project_idea.md

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+---
+name: New GSoC Project Idea
+about: Template for a GSoC project idea
+title: 'gsoc: project: '
+labels: gsoc
+assignees: ''
+
+---
+
+# Project Name
+
+AutoML or Automated Machine Learning as the name suggests automates the process
+of solving problems with Machine Learning. AutoML is generally helpful for
+people who aren't either familiar with Machine Learning or the involved
+programming. AutoML aims to improve the efficiency of any task involving
+Machine Learning.
+
+The primary objective we are trying to achieve is to create a model that
+takes as a property of its config a set of models to used for hyperparameter
+tuning. Another property of its config is the set of models which we should
+attempt to tune (via the first set). Default values for these results in using
+all installed models to try to tune all installed model plugins.
+
+- To start, we should define a reduced set of models (not all the ones we have).
+  We'll implement AutoML supporting only this reduced set. The first phase of
+  this project will be to make sure that one model can be used to tune
+  hyperparameters of another model.
+
+- The next phase will be to tune two models using the same tuning model. This
+  followed by tuning two models, using two models which amounts to doing the
+  previous task twice, with a different tuning model the second time.
+
+- The following phase will be to go through each model in each model plugin we
+  have and see which ones have issues being tuned using the approach taken in the
+  previous phase. This phase will help us determine which properties or methods
+  we may need to add to models to help them self identify and thereby indicate
+  their requirements for hyperparameter tuning, or maybe their inherent lack of
+  support for it.
+
+- The final phase will be to implement hyperparameter tuning for N by N models,
+  after implementing what we found to be gaps in the previous phase.<br>
+
+Due to the shortened GSoC cycle, we may end up not doing all of these phases.
+Which one we go to will be decided as we approach the selection process.
+
+## Skills
+
+- Python
+- Intermediate Machine Learning
+- Experience with various machine learning frameworks (AutoML frameworks would
+  be a plus)
+
+## Difficulty
+
+Intermediate/Hard
+
+## Estimated Time Required
+
+175|350 hours
+
+## Related Readings
+
+- https://github.com/intel/dffml/blob/master/docs/contributing/gsoc/2021.md
+- https://scikit-learn.org/stable/model_selection.html#model-selection
+- https://www.automl.org/automl/
+
+## Getting Started
+
+- Read the contributing guidelines
+  - https://intel.github.io/dffml/master/contributing/index.html
+- Go through the quickstart
+  - https://intel.github.io/dffml/master/quickstart/model.html
+- Go trough the model tutorials
+  - https://intel.github.io/dffml/master/tutorials/models/
+- Go through the model plugins
+  - https://intel.github.io/dffml/master/plugins/dffml_model.html
+  - You don't need to go through all of them. Just get a feel for running a few
+
+## Potential Mentors
+
+- [John Andersen](https://github.com/pdxjohnny)
+- [Saahil Ali](https://github.com/programmer290399)
+- [Yash Lamba](https://github.com/yashlamba)
+- [Saksham Arora](https://github.com/sakshamarora1)