These data sets provide a higher level of complexity and difficulty, and help in building upon the solid basics acquired by working with simpler data sets. This data set comes from the Boston-based bicycle sharing service, Hubway.
Variables within the data include duration, membership type, gender, and destinations among others. The data provides an engaging exercise in data wrangling and serves as a classification problem Objective: Provide a visualization of the data answer questions on user patterns.
Large amounts of unstructured data is found within natural language.
The goal is to use recipe ingredients to categorize cuisines. Text mining data sets test skills on classification and clustering. Occasionally, regression analysis may be required. Classification and categorisation based on tags or labels. It contains the extracted weighted census data, and has 41 employment and demographic related variables.
While the the original table containedrows and 42 columns, the newer refined versions of the data set contain anywhere between columns and above 30, rows.
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It is a commonly cited data set of KNN know nearest neighbors and is a classification problem. The smallest set meant for the purpose of education and development containsratings and 1, tag applications applied to 9, movies by users.
While the largest set meant for the same purpose contains 26, ratings andtag applications applied to 45, movies byusers. It also contains stable benchmark data set of 20 million ratings andtag applications applied to 27, movies byusers. Make movie suggestions for users. After acquiring the necessary basics and honing them in the first two levels, it is time to confidently play the big game.
These data sets provide a platform for putting to use all the learnings and take on new, and more complex challenges.
Inthe tenth round of the Yelp Dataset Challenge was held and the data set contained information about local businesses in 12 metropolitan areas across 4 countries. Provide insights for operational improvements using the data available. This presents a herculean task for a data scientist with limitation of time.
Not included in the data set, is data on murder, where data is recorded for each victim.
In order to achieve mastery over working with abundant data, this data set can serve as the ideal stepping stone in the pursuit of tackling mountainous data.
Explore the data, and provide insights and forecasts about crimes in Chicago. It is considered to be the first-ever data science competition held and dates back to With a different problem every year, the KDD cup provides data scientists an opportunity to work with data sets across different disciplines.
The latest edition of the challenge was held in and required participants to predict the traffic flow through highway tollgates.
Solve or make predictions for the problem presented every year. Held annually, the primary aim of the competition is the comparison of progress in the area of image detection and classification, and merging good research with more data.
It also aims to measure the progress made in indexing for retrieval and annotation by computer vision. This challenge assess algorithms for object detection and localization, from videos and images, and scene parsing and classification on a large scale.
Every year, the challenge sees modifications such as addition of new images and categories. The visual resource available consists of overobjects for classification from over ,00 images that have been gathered from Flickr and other search engines.You may have arrived at this page because you followed a link to one of our old platforms that cannot be redirected.
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