[Student DataFest 2018] Skilltest - Ensemble Learning

The topic which you should probably know about when you want to become a data science practitioner is ensemble learning - which essentially is a powerful way to improve the performance of your predictive models.

This week's skilltest focuses on the intuition behind doing ensembling, and basic concepts and ideas of ensemble learning.

The topics covered in the skilltest are the following:

• Basics of Ensembling
• Commonly used Ensemble learning techniques
  • Bagging models
  • Boosting models

You can avail a maximum of 150 AV points.

This is the last week of your learning, but this doesn't mean that you have to stop there. There is so much more out there that is just waiting to get explored by people like you. This week's skill-test specifically focuses on the advanced concept that was covered in the week, aka ensemble learning

The skilltest is based on the course 'Introduction to Data Science' in regards to Student DataFest 2018. Please go through the course before attempting the skilltests, as you will not be able to retake the skilltest once started"

Rules

• The questions are MCQ types. Each question carries equal marks.
• There is no negative marking for any wrong answer.
• There is only one option correct for each question.

FAQs

1. Who is a student?
   Any one undergoing a course from a recognised university or college with graduation date on or after15th May 2018will be considered as a student.
   
   
2. I am undergoing a part time course, will I be considered as student?
   No
   
   
3. I am a student, but I am unable to register for this hackathon?
   First, create a profile on Analytics Vidhya (SignUp) and then register yourself as a Student here.
   
   
4. What do you need in a Photo id?
   A photo id is an identification issued by your college / university acknowledging that you are a student. The id would typically have your roll number, start date and end date
   
   
5. How long will it take to be verified as a student?
   We will do it with in a couple of days. Normally, it is faster than that.