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Choose and convert one of the categorical column data to numeric values

INSTRUCTIONS TO CANDIDATES
ANSWER ALL QUESTIONS

PROJECT

Title:

Construct baseline model for training and evaluating models using ML Tools.

Tools, Equipment and Materials:

1 Windows PC with Python editor, Python compiler, MSOffice installed, Web Browser.

Instructions:

You have to construct and test a ML (Machine Learning) model.

1 Browse to kaggle.com website to search for ‘binary categorical data’ where the target is a binary value.

2 Choose and download one of the listed datasets from the search results to predict the binary target.

3 Write a script to cleanse the downloaded datasets for the following from at least one of the columns:

a. Invalid data

b. Null values

c. Unknown values

4 Choose and convert one of the categorical column data to numeric values.

5 Create datasets from csv files using the required features and target.

6 Choose between supervised and unsupervised method for machine learning for the downloaded dataset.

7 Choose an appropriate machine learning algorithm to predict the binary target.

8 Build the model using the dataset and specify the appropriate parameters for the algorithm chosen in Step 7.

9 Select training data and test data from the dataset. 

10 Train the machine learning model using the selected algorithm and dataset.

11 Use the test data selected in Step 9 to evaluate the model.

12 Demonstrate the results using the following parameters.

a. Accuracy of prediction

b. False Positives

c. False Negatives

d. True Positives

e. True Negatives 

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