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Language Recommendation #74
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Assigned you @iABn0rma1 and this is interesting. |
Hi, I'd love to collaborate with @iABn0rma1 on this. |
Hi @sanjay-kv I would like to work in this issue . |
Hi @sanjay-kv according to @iABn0rma1 proposal which is New developers often get confused when choosing the right programming language for career development or a project. However, his proposal typically focus on general recommendations without considering community trends and job market dynamics. My proposal aims to introduce a language recommendation system that leverages community insights and real-time job market analysis. My Solution Using Stack Overflow survey data combined with job market trends, I propose a dynamic language recommendation model that not only considers individual preferences and backgrounds but also adapts to current industry demands and community trends. Features
What Problems the above features will trying to solve
Approach
We will be consider this model if we got more accuracy and personalization strategy. I would love to contribute on this. Thank you |
Can u guys collaborate? |
Sure, @sanjay-kv. We both can work on this |
@sanjay-kv @barlasanjay |
Thank you @iABn0rma1 and @sanjay-kv please assign this task to both of us |
Can I join , @sanjay-kv @iABn0rma1 , I would like to work under this issue. |
can i join,@sanjay-kv @iABn0rma1 ?i want to contribute in this issue |
@iABn0rma1 are you still working on it. |
Is your feature request related to a problem? Please describe.
New developers often get confused when choosing the right programming language for career development or a project.
Describe the solution you'd like
Leveraging the Stack Overflow data, I propose a personalised language recommendation model. Factors such as experience level, project requirements and area of interest are important to make the prediction.
Describe alternatives you've considered
An alternative approach will suggest languages based on the preferences of similar developers.
What problem is this feature trying to solve?
It considers programmers' preferences, individual needs, and goals to help them tackle the difficulties faced in choosing the right programming language.
How do we know when the feature is complete?
The feature can be considered complete when the model demonstrates the following:
Accuracy: The recommendations align with user expectations and preferences.
Personalisation: Adapts to individual needs and preferences, providing different suggestions to different users.
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