Data Science Chartbusters Prediction Hackathon: Predict Popularity Of Songs &#038; Win Exciting Prizes
“Without music, life would be a mistake” – Friedrich Nietzsche Music has been tightly embedded in our system since the beginning of time as we know it. It has its presence in every culture known to humankind from ancient tribes to modern civilizations. Today, music has grown to be an industry by itself, not just an industry, but something that contributes to the world’s economy in millions or possibly in billions of dollars. Music is deeply influenced by the advancement in technology. Machine learning (ML) and artificial intelligence (AI) are prevalent in the industry today, and machines are capable of even generating its own music. ML and AI also power intelligent recommender systems that provide a customised experience to each listener based on his/her likes. The world listens to millions and billions of songs every day on varied platforms, all of which is being recorded and closely observed to find patterns in human behaviour towards different styles of music. This helps the platforms to recommend the best songs to the users based on their history of likings and listening pattern. Spotify, Youtube Music, Amazon and many other music platforms are now backed by recommender systems that do nothing but provide the best experience by recommending the right music to the right user. In this hackathon, we will explore the data collected from various sources to find interesting patterns in the behaviour of people towards different styles of music. CHARTBUSTERS PREDICTION: FORETELL POPULARITY OF SONGS One of our customers strongly believes in technology and has recently backed up its platform using machine learning and artificial intelligence. Based on the data collected from multiple sources on different songs and various artist attributes, our customer is excited to challenge the MachineHack community. By analysing the chartbusters’ data to predict the views of songs, MachineHackers would advance the state of the current platform. This can help our customer understand user behaviour and personalise the user experience. In this hackathon, we challenge the MachineHackers to come up with a prediction algorithm that can predict the views for a given song. Can you predict how popular a song will be in the future? To participate in the hackathon click here. About The Dataset Size of training set: 78458 records Size of test set: 19615 records FEATURES: Unique_ID : Unique identifier.Name: Name of the artist.Genre: Genre of the song.Country: Origin country of the artist.Song_Name: Name of the song.Timestamp: Release date and time.Views: Number of times the song was played/viewed (*Target/Dependent Variable*).Comments: Count of comments for the song.Likes: Count of likes.Popularity: Popularity score for the artist.Followers: Number of followers. MachineHack as a platform is dedicated to bringing out the best in the growing data science community. The data is gathered from credible sources and we welcome all the young data scientists out there to explore the world of data till you become good at it. Challenge yourself with this hackathon, learn a lot and win exciting prizes. To participate in the hackathon click here. Hackathon Rules One account per participantSubmissions from multiple accounts will lead to disqualification.Users may submit the solution any number of times before the specified hackathon expiry date.You will not be able to submit once you click the “Complete Hackathon” button. You may ignore this feature.This hackathon closes on January 15, 2020.This hackathon is open to all registered users who are 18 years or older.This competition counts towards our overall ranking points. We ask that you respect the spirit of the competition and do not cheat.The winners will be asked to submit code at the end of the hackathon period. Participants using automated ML platforms will be disqualified. Prizes The top 3 contestants will receive a free pass to Machine Learning Developers Summit 2020 – INDIA’S FIRST CONFERENCE EXCLUSIVELY FOR MACHINE LEARNING PRACTITIONERS ECOSYSTEM Machine Learning Developers Summit 2020 (MLDS-20) brings together India’s leading Machine Learning innovators and practitioners to share their ideas and experiences about machine learning tools, advanced development in this sphere, and gives the attendees a first look at new trends and developer products. To participate in the hackathon click here. How To Register Head to MachineHack and sign up. Select Hackathons and click on ‘Chartbusters Prediction: Foretell The Popularity Of Songs‘. For detailed instructions on how to use MachienHack read the below article: HOW TO GET STARTED WITH MACHINE HACK, A-DATA SCIENTIST’S DESTINATION FOR COMPETITIONS and PRACTISE To participate in the hackathon click here.
“Without music, life would be a mistake” – Friedrich Nietzsche Music has been tightly embedded in our system since the beginning of time as we know it. It has its presence in every culture known to humankind from ancient tribes to modern civilizations. Today, music has grown to be an industry by itself, not just […]
This ML hackathon challenges the MachineHackers to come up with a prediction algorithm that can predict the views for a given song.
["Challenge", "Data Science", "Hackathon", "Hackathons India", "Machine Learning"]
["Challenge", "data science", "Go", "artificial intelligence", "machine learning", "programming_languages:R", "AI", "R", "ML", "Machine Learning", "programming_languages:Go", "Hackathon", "Data Science", "Hackathons India"]
["AI", "artificial intelligence", "machine learning", "ML", "data science", "R", "Go", "programming_languages:R", "programming_languages:Go"]
A Computer Science Engineer turned Data Scientist who is passionate about AI and all related technologies. 
Contact: amal.nair@analyticsindiamag.com