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Context The comp - activ database comprises activity measures of computer systems. Data was gathered from a Sun Sparcstation 2 0 / 7 1 2

  
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The comp-activ database comprises activity measures of computer systems. Data was gathered from a Sun Sparcstation 20/712 with 128 Mbytes of memory, operating in a multi-user university department. Users engaged in diverse tasks, such as internet access, file editing, and CPU-intensive programs.

Being an aspiring data scientist, you aim to establish a linear equation for predicting 'usr' (the percentage of time CPUs operate in user mode). Your goal is to analyze various system attributes to understand their influence on the system's 'usr' mode. Problem 1- Define the problem and perform exploratory Data Analysis
- Problem definition - Check shape, Data types, statistical summary - Univariate analysis - Multivariate analysis - Use appropriate visualizations to identify the patterns and insights - Key meaningful observations on individual variables and the relationship between variables
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Problem 1- Data Pre-processing
Prepare the data for modelling: - Missing Value Treatment (if needed)- Outlier Detection (treat, if needed)- Feature Engineering - Encode the data - Train-test split
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Problem 1- Model Building - Linear regression
- Apply linear Regression using Sklearn - Using Statsmodels Perform checks for significant variables using the appropriate method - Create multiple models and check the performance of Predictions on Train and Test sets using Rsquare, RMSE & Adj Rsquare.
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Problem 1- Business Insights & Recommendations
- Comment on the Linear Regression

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