Related Questions

In machine learning, what is the term for the process of reducing the dimensionality of data while preserving as much information as possible?
In data modeling, what is the term for the process of reducing the dimensionality of data while preserving its important features?
In Data Science, what is the term for the process of reducing the dimensionality of a dataset while preserving information?
Which of the following statements are true?
Statement I Big data refers to no precise quantity, but generally refers to data in the range of Petabytes and Exabyte, i.e. billions to trillions of records, all from various sources. Big data is generated much faster. than traditional data in much larger quantities.
Statement II Big data interests industries because they are able to learn more patterns and curious variances than smaller data sets, with the capability to provide valuable insights into consumer behaviour, weather systems, financial market activity, or other phenomena.
Statement III Various departments and product lines use various applications within most organisations and store data in separate datasets. These separate databases may contain similar data, but data from one data base to another is not always consistent. This is called data silo.
What is the term for the process of reducing the dimensionality of data while retaining its most important features?
In data science, what is the term for the process of converting text data into numerical form while preserving semantic meaning?
Which one of the following is true with regard to a CPU having a single interrupt request line and single interrupt grant line? i) Neither vectored nor multiple interrupting devices is possible. ii) Vectored interrupts is not possible but multiple interrupting devices is possible. iii) Vectored interrupts is possible and multiple interrupting devices is not possible. iv) Both vectored and multiple interrupting devices are possible.
The most popularly used dimensionality reduction algorithm is Principal Component Analysis (PCA). Which of the following is/are true about PCA?
1. PCA is an unsupervised method
2. It searches for the directions that data have the largest variance
3. Maximum number of principal components 4. All principal components are orthogonal to each other
In data science, what is the term for the process of reducing the volume of data while retaining meaningful information?
You use Microsoft Visual Studio 2010 and Microsoft .NET Framework 4 to create anapplication. The application uses the ADO.NET Entity Framework to model entities. Theapplication allows users to make changes to entities while disconnected from the central data store. You need to ensure that when the user connects to the central data store and retrieves new data, the application meets the following requirements:
  • Changes made to the local data store in disconnected mode are preserved.
  • Entities that have already been loaded into the local data store, but have not been modified by the user, are updated with the latest data.
What should you do?