test comp with custom evaluator | bitgrit
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test comp with custom evaluator

Test
3 Participants
5 Submissions
Brief
Timeline
Data Breakdown
FAQs
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 five submissions per day. If users want to submit new files after making five 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. Any attempt to circumvent stated limits will result in disqualification. 3. The use of external datasets is not allowed. 4. It is not allowed to upload the competition dataset to other websites. Users who do not comply with this rule will be disqualified. 5. A competition prize will be awarded after we have received, successfully executed, and confirmed the validity of both the code and the solution. Once winners are announced and our team reaches out to them, the winners must provide the following by July 13, 2021 to be qualified as a competition winner and receive their prize: a. All source files required to preprocess the data b. All source files required to build, train and make predictions with the model using the processed data c. A requirements.txt (or equivalent) file indicating all the required libraries and their versions as needed d. A ReadMe file containing the following: • Clear and unambiguous instructions on how to reproduce the predictions from start to finish including data pre-processing, feature extraction, model training and predictions generation • Environment details regarding where the model was developed and trained, including OS, memory (RAM), disk space, CPU/GPU used, and any required environment configurations required to execute the code • Clear answers to the following questions: - Which data files are being used? - How are these files processed? - What is the algorithm used and what are its main hyperparameters? - Any other comments considered relevant to understanding and using the model
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Step 1
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Your submission should be in .csv format.
Step 2
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