What are some of the popular data sets available for machine and deep learning?

Machine Learning Datasets for Natural Language Processing

• Enron Email Dataset. This Enron dataset is popular in natural language processing.
• The Yelp Dataset.
• Jeopardy Dataset.
• Recommender Systems Dataset.
• UCI Spambase Dataset.
• Flickr 30k Dataset.
• IMDB reviews.
• MS COCO dataset.

What are the different types of datasets?

Types of Data Sets

• Numerical data sets.
• Bivariate data sets.
• Multivariate data sets.
• Categorical data sets.
• Correlation data sets.

Which machine learning is provided with the labeled past dataset?

The set of algorithms in which we use a labeled dataset is called supervised learning.

What are datasets in machine learning?

A dataset in machine learning is, quite simply, a collection of data pieces that can be treated by a computer as a single unit for analytic and prediction purposes. This means that the data collected should be made uniform and understandable for a machine that doesn’t see data the same way as humans do.

What are datasets used for?

Data sets can hold information such as medical records or insurance records, to be used by a program running on the system. Data sets are also used to store information needed by applications or the operating system itself, such as source programs, macro libraries, or system variables or parameters.

What is a dataset?

A data set (or dataset) is a collection of data. In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question.

What are labeled datasets?

Labeled data, used by Supervised learning add meaningful tags or labels or class to the observations (or rows). These tags can come from observations or asking people or specialists about the data. Classification and Regression could be applied to labelled datasets for Supervised learning.

What is labeled data with example?

For example, a data label might indicate whether a photo contains a horse or a cow, which words were uttered in an audio recording, what type of action is being performed in a video, what the topic of a news article is, what the overall sentiment of a tweet is, or whether a dot in an X-ray is a tumor.

Are public image datasets the answer to the computer vision bottleneck?

However, the scarcity of public image datasets remains a crucial bottleneck for fast prototyping and evaluation of computer vision and machine learning algorithms for the targeted tasks. Since 2015, a number of image datasets have been established and made publicly available to alleviate this bottleneck.

How many actions are there in the Cornell activity dataset?

Cornell Activity Datasets CAD 60, CAD 120 (Cornell Robot Learning Lab) DMLSmartActions dataset – Sixteen subjects performed 12 different actions in a natural manner (University of British Columbia) Depth-included Human Action video dataset – It contains 23 different actions (CITI in Academia Sinica)

Why make datasets publicly available?

Making datasets publicly available saves the significant resources associated with data preparation, and also enables benchmarking of image analysis and machine learning algorithms developed among different research groups ( Lobet, 2017 ).

What datasets are not suitable for precision agriculture applications?

These datasets that consist of images from the Internet sources or for natural scenes or objects, however cannot directly translate to precision agriculture applications.