Janatahack: Machine Learning in Agriculture

Recently we have observed the emerging concept of smart farming that makes agriculture more efficient and effective with the help of high-precision algorithms. The mechanism that drives it is Machine Learning — the scientific field that gives machines the ability to learn without being strictly programmed. It has emerged together with big data technologies and high-performance computing to create new opportunities to unravel, quantify, and understand data intensive processes in agricultural operational environments.

Machine learning is everywhere throughout the whole growing and harvesting cycle. It begins with a seed being planted in the soil — from the soil preparation, seeds breeding and water feed measurement — and it ends when neural networks pick up the harvest determining the ripeness with the help of computer vision.

This weekend get ready to harness the power of ML to solve a problem based in agriculture and get a chance to showcase your skills and win AV points!

FAQs

1. Where can I find the dataset and the problem statement for the hackathon?

The contest will go live on the designated contest start date and time. There is a timer that is shown at the top of this page which shows the remaining time before the contest goes live. This is when you can access the problem statement and datasets from the problem statement tab.

2. Can I share my approach/code?

Absolutely. You are encouraged to share your approach and code file with the community. There is even a facility at the leaderboard to share the link to your code/solution description.

3. I am facing a technical issue with the platform/have a doubt regarding the problem statement. Where can I get support?

Join the AV slack channel by clicking on 'Join Slack Live Chat' button and ask your query at channel: janata_hack