Weather Forecast Challenge | bitgrit
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Weather Forecast Challenge

Predict the weather and feed the world

bitgrit
8 Participants
19 Submissions
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Brief
This is a learning competition. Aside from knowledge, there is no monetary prize at stake. Since the dawn of time, human beings have been trying to keep tabs on mother nature. For basic survival and protection, to mega industries like construction and transportation, weather forecasting is crucial to our survival! The things is— it’s not exactly an easy task. In fact, the prediction of the weather has been subject to human error time and time again simply because of the sheer volume of data that must be processed. One place where forecast precision is imperative is in the agricultural sector. Farmers make daily decisions based on the weather, and these decisions can have massive impact on the health and vitality of their yield, and the world. Here is where you come in… Problem Statement: A major agricultural company needs you to help them maximize growth efficiency, save resources and optimize their production. To achieve these things, the company needs to have an accurate weather prediction algorithm which will improve their decision making on typical farming activities such as planting and irrigating. Using historical weather information from their region, can you predict what the weather will be in the next few days? This is a beginner-level practice competition and your goal is to predict the next day’s weather (N: No rain L: Light rain H: Heavy rain) using the prior day’s weather data.
Timeline
  • 09 Mar 2022 Competition Starts
Data Breakdown
The goal of this competition is to predict the next day’s weather (N: No rain L: Light rain H: Heavy rain) using the prior day’s weather data. In order to build your machine learning model, we have provided the following data sets: There are 2 datasets for this competition, train datasets and test datasets. Both datasets have weather data for region A through region E. These region datasets can be joined with the solution file using the 'date' column. Your goal is to build the algorithm(s) that predicts the "label" in the solution_format.csv. Please note that all the values in the solution_format.csv are dummy values. *All "dates" are anonymized. **The submission file should follow the same format as the example file (solution_format.csv). Submissions are evaluated on accuracy (that is, 'Number of correct predictions / Total Number of predictions). NOTE: You may submit a solution file up to 3 times a day.
FAQs
Who do I contact if I need help regarding a competition?
For any inquiries, please contact us at [email protected]
How can I report a bug?
Please shoot us an email at [email protected] with details and a description of the bug you are facing, and if possible, please attach a screenshot of the bug itself.
If I win, how can I receive my reward?
This is a learning competition. Aside from knowledge, there are no prizes for this competition.
Rules
1. This competition is governed by the following Terms of Participation. Participants must agree to and comply with these Terms to participate. 2. Users can make a maximum number of 3 submissions per day. If users want to submit new files after making three submissions in a day, they will have to wait until the following day to do so. Please keep this in mind when uploading a submission.csv file. 3. The use of external datasets is not allowed. 4. It is not allowed to upload the competition dataset to other websites. 5. All submissions need to be made as an individual; no teams are allowed in this competition. 6. This competition has a rolling leaderboard of 90 days. Once a submission is more than 90 days old, it will no longer counts to the leaderboard. 7. This competition is for learning and exploring. Aside from knowledge, there are no prizes for this competition. 8. If you have any inquiries about this competition, please don’t hesitate to reach out to us at [email protected].
New Submission
Step 1
Upload or drop your file
Upload or drop your csv file here.
Your submission should be in .csv format.
Step 2
Description
Briefly describe your submission (400 characters or less)

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