Learning Objectives
- In this task, we will explore:
- Different steps in a generic Machine Learning pipeline
- Machine Learning classification and training models
- How to split the dataset into training and testing data
- How to prepare the Machine Learning model
- How to evaluate the model's effectiveness
This is the continuation of Day 14.
After the machine is up.
Run all the cell.
QUESTIONS
- What is the key first step in the Machine Learning pipeline?
Answer
Data Collection
- Which data preprocessing feature is used to create new features or modify existing ones to improve model performance?
Answer
Feature Engineering
- During the data splitting step, 20% of the dataset was split for testing. What is the percentage weightage avg of precision of spam detection?
Answer
0.98
- How many of the test emails are marked as spam?
Answer
3
- One of the emails that is detected as spam contains a secret code. What is the code?
Answer
I_Hate_BesT_FestiVal
