Flowers

Data Science Blogathon - 14

Online 08-11-2021 12:00 AM to 30-11-2021 11:59 PM
  • 405

    Registered

  • Assured Rewards + Total prizes worth INR 5 Lakh(≅USD 7000)

    Prizes

Data Science Blogathon returns with a lot of fanfare!

Having published over 1600 articles on various topics in Data Science, Machine Learning, Deep Learning, Data Engineering, etc., we continue to be the talk of the town! Over 500 authors from all over the world are a part of our thriving community. Are you ready to join this international community?


What are the Prizes on offer?

Choose the Data Science content you want to create and win for each published article - there's no minimum views threshold this time!

Submission Type Minimum Length of Text Topic Base Reward for Creators Club Members Base Reward for non-members
Article 1000 words Deep Learning, CV, NLP, Data Engineering, MLOps INR 1,800(≅USD 24) INR 1,500(≅USD 20)
Any Other Topic INR 1,200(≅USD 16) INR 1,000(≅USD 13)
Guide 2500 words No Constraints(please refer to suggestions below) INR 3,000(≅USD 40) Not Applicable

* Publish 3 or more articles in any Data Science Blogathon and automatically become a part of the Anaytics Vidhya Creators' Club to avail exciting benefits and prizes!

* Note that the article will have to be technical and code-based in nature to be eligible for the above special categories. Listicles or career articles will not count.

* All International payments will be made via Paypal

What's at stake?

  • The top 3 Articles will be judged based on the number of unique pageviews
  • The top 3 Guides will be judged by the editorial team

Submission Type Rank Winners Prize
Articles img INR 10,000(≅USD 133)
img INR 5,000(≅USD 66)
img INR 3,000(≅USD 40)
Guides* img INR 7500(≅USD 100) each
* 3 Guides (Chosen by Editors)

And that's not all! More Prizes!

Submission Type Views Bonus Rewards
Article and Guide 5000 to 15000 INR 1,000(≅USD 13)
>15000 INR 2,000(≅USD 26)


A New Submission Category - Guides!

As mentioned above, we are introducing a new type of submission this time, called "Guides". Guides are intended to be a one-stop resource on specific topics in Data Science, Machine Learning and related topics. Since we receive multiple entries for Guides, only one Guide per topic will be published.

Guide Topics Guide Topics Guide Topics Guide Topics
End-to-End Machine Learning Model using Julia A Comprehensive Guide on Building an ETL Pipeline for Beginners A Detailed Case Study using Geospatial Analysis A Complete Guide on ggplot
A Comprehensive Guide on Building Bots using Python A Complete Guide on Kubernetes A Detailed Study on Covid-19 Vaccinations data How to deal with Sparse Datasets
Building an End-to-End Multiclass Text Classification Model A Comprehensive Guide on using Django for Data Science Building an End-to-End Polynomial Regression Model A Comprehensive Guide on Recommendation Engines
A Comprehensive Guide on Building Chatbots A Comprehensive Guide on using AWS for Data Science End-to-End Predictive Analysis on Zomato A Comprehensive Guide on Graph Neural Networks
A Comprehensive Guide on ML Interpretability Techniques and Tools A Comprehensive Guide on using RedShift A Comprehensive Guide on Replication in Data Engineering A Comprehensive Guide on Causal Inference
A Comprehensive Guide on Federated Learning A Detailed Guide on SQL Query Optimisation A Comprehensive Guide on Sharding in Data Engg. A Comprehensive Guide on Neo4j
A Comprehensive Guide on Markov Chain A Complete Guide on using MongoDB for Data Science A Comprehensive Guide on Partitioning in Data Engg. An End-to-end Guide on Anomaly Detection
A Complete Guide on PowerBI A Comprehensive Guide on Feature Engineering A Comprehensive Guide on Microsoft Excel for Data Analysis A Comprehensive Guide on using AzureML
A Comprehensive Guide on using KNIME A Comprehensive Guide on Optuna A Comprehensive Guide on Machine Learning for Mobile Devices A Comprehensive Guide on using Flask for Data Science


Here is an example of a Guide: K Means Clustering | K Means Clustering Algorithm in Python

Feel free to explore any topic of your choice though - the only restriction is that it should be as comprehensive as possible and should be of a minimum of 2500 words in length. It should also be on a topic in the domain of Machine Learning, Data Science, Deep Learning, Data Engineering, etc.


How do I Participate?

To enter the competition, just press the register button above. Once the competition starts on November 8th, please head over to https://editor.analyticsvidhya.com/ and start writing. It's that simple!

Note that it takes us up to 36 hours to review and provide feedback for each article. And once you see ‘Shortlisted’ on the Editor, give it up to 6 hours for the article to reflect on the Analytics Vidhya blog.


What are the important dates & deadlines?

Nov 8, 2021 Nov 30, 2021
11:59 P.M. IST
(GMT + 5:30 hrs)
Dec 7, 2021
11:59 P.M. IST
(GMT + 5:30 hrs)
Dec 7, 2021
11:59 P.M. IST
(GMT + 5:30 hrs)
Dec 9, 2021
Registration Begins Registration Ends Submission Ends Views will be counted till this date Winners Announcement


Note: We update the leaderboard twice a day. There is no set time for the update per se. But check back in the afternoon and late evening to see the latest views.

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