[Student DataFest 2018] Skilltest - Ensemble Learning
About the Event
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
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
- 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. - I am undergoing a part time course, will I be considered as student?
No - 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. - 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 - 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.
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Participants benefit from one-on-one feedback, publication on a respected platform, recognition from a global audience, and monetary rewards for each published article. Additionally, the top articles receive special rewards.
Each article must be original, and pass plagiarism and not AI generated content checks. You can submit multiple articles as long as each is distinct. Proper citation of all references and image sources is mandatory.
There are no specific requirements to register for the hackathon, although it is recommended to have some basic knowledge of the relevant topics, such as Data Science, Machine Learning, or Deep Learning, along with proficiency in a coding language, preferably Python.
In the Blogathon, an article typically explores a specific topic or idea within Data Science or Generative AI and is required to be at least 1000 words long. A guide, on the other hand, is a more comprehensive resource, covering all aspects of a particular subject in data science, and must be at least 2500 words long. Guides aim to serve as a one-stop resource, providing detailed insights and practical applications, whereas articles might focus on narrower or more specific topics.
Depending on the type of competition, you can participate individually or in a team.
Multiple submissions of the same article are prohibited and could lead to disqualification. Articles failing to meet the required length, originality, or citation standards will be rejected.
AVCC is a community for authors who have had three or more articles published in the Blogathons. Members benefit from monetary rewards for each published article and get the opportunity to showcase their work to a larger audience.
You can access the problem statement under the "Problem Statement" tab once the Hackathon is live.
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