Kluster

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AI/ML

Precision Farming for Best Product Results with Data

Summary

Build a solution that predicts the best time to plant and harvest crops, taking into account local weather conditions and soil quality. This solution will help farmers improve their yields.

Requirements

Farmers should be able to enter their location and crop details.
Create a system that uses machine learning to predict the best planting and harvesting times.
Make it user-friendly so even non-tech-savvy farmers can use it.
Find the Data for building here.

Submission Guidelines

Figma (Optional): Provide a link to your Figma design / prototype for your project.
GitHub Repository: Provide the link to your GitHub repository containing all the relevant source code and project files.
Deployed Link: Share the link to the deployed version of your project. For web applications, consider hosting on platforms like Netlify or Heroku. If it's a mobile app, upload the APK to Google Drive and provide a public link.
Walkthrough/Presentation: Create a concise 2 to 5-minute maximum screen recording. Walk through key features, functionalities, and any unique aspects of your project. Clearly articulate how users can interact with and benefit from your solution. Ensure your presentation covers essential details without exceeding the time limit.

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Explore Models

You have the freedom to explore a wide range of models for your project. Not limited to the following options:

Suggested Approach

Day 1 - 2: Conceptualization & Design

Data Science AI/ML:

Research and select appropriate machine learning models for yield prediction.
Identify key environmental factors impacting crop yield.

Product Manager & Product Designer:

Define the user flow for farmers to input location and crop details.
Design an intuitive and user-friendly interface for non-tech-savvy users.

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Day 3 - 4: Development & Testing

Frontend:

Develop a straightforward interface for farmers to input data easily.
Ensure the system is accessible to non-tech-savvy users.

Backend:

Implement the backend system for data storage and retrieval.
Integrate selected machine learning models for yield prediction.

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Day 5 - 6: Refinement, User Feedback Integration, & Presentation

All Team Members:

Integrate farmer feedback mechanisms for usability improvements.
Conduct extensive testing for reliability and ease of use.
Finalize the project, focusing on simplicity, accuracy, and user satisfaction.

Prepare a Presentation:

Showcase the solution's capabilities, emphasizing its potential impact on improving crop yields for farmers.

Build a solution that predicts the best time to plant and harvest crops, taking into account local weather conditions and soil quality. This solution will help farmers improve their yields.

Access Free OpenAI API Keys!

Explore Models

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Day 1 - 2: Conceptualization & Design

Data Science AI/ML:

Product Manager & Product Designer:

Day 3 - 4: Development & Testing

Frontend:

Backend:

Day 5 - 6: Refinement, User Feedback Integration, & Presentation

All Team Members:

Prepare a Presentation:

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