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About Contest
This Contest helps students to get exposed to tools and technologies used in Data Science, Analytics like Altair Knowledge Studio. This FREE* Contest program is meant for individual students (UG / PG / Ph.D.) of all branches of Engineering specifically designed for the Students participating in Techkriti'22.
Contest Details
A real estate company wants to use its historical data to predict the sales price for each house. You need to analyze the relevant customer data using Knowledge Studio. For each Id in the test set, you must predict the value of the Sale Price variable.
Competition Description
Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.
With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home
Objective: Try different ML models that will help to predict the final price of each home. It would help the real estate company to understand the requirement of home buyers and will help them to buy their dream house.
- Import the data: [5 Points]
a. Import dataset_1 and dataset_2 and append
b. Explore the final shape and size of data. - Data Cleanup: [5 points]
a. Missing value treatment
b. Convert categorical columns to continuous columns (if required)
c. Drop attribute/s (if required) - Data analysis and visualize: [10 points]
a. Write the conclusion about the distribution of data and you're understanding.
b. Determine which factors influence the churning of the data with evidence. - Data pre-processing: [5 points]
a. Segregate prediction and target attribute
b. Perform train test split
c. Check if the train and test data have similar statistical characteristics when compared with original data - Model training, testing, and tuning: [15 points]
a. Train and test all the supervised models present in Knowledge studio.
b. Display and compare all the models designed with their train and test accuracies
c. Select the final best-trained model along with detailed comments for selecting the model.
d. Score using a final selected model on the new validation_data using scoring node - Conclusion and improvisation: [10 points]
a. Write a detailed conclusion on your results
b. Detailed suggestions or improvement on the quality, variety, etc. on the data points collected by the real estate dealer to perform better data analysis in the future. - Altair Knowledge Studio Certification course completion certificate [10 Points]
- Download the model file info from this link.
Contest Schedule
