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  2. Andrew Ng - Wikipedia

    en.wikipedia.org/wiki/Andrew_Ng

    His machine learning course CS229 at Stanford is the most popular course offered on campus with over 1,000 students enrolling some years. [24] [25] As of 2020, three of most popular courses on Coursera are Ng's: Machine Learning (#1), AI for Everyone (#5), Neural Networks and Deep Learning (#6). [26]

  3. Apache Hadoop - Wikipedia

    en.wikipedia.org/wiki/Apache_Hadoop

    Apache Hadoop (/ h ə ˈ d uː p /) is a collection of open-source software utilities for reliable, scalable, distributed computing.It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.

  4. Data engineering - Wikipedia

    en.wikipedia.org/wiki/Data_engineering

    Around the 1970s/1980s the term information engineering methodology (IEM) was created to describe database design and the use of software for data analysis and processing. [3] [4] These techniques were intended to be used by database administrators (DBAs) and by systems analysts based upon an understanding of the operational processing needs of organizations for the 1980s.

  5. Coursera - Wikipedia

    en.wikipedia.org/wiki/Coursera

    A free course can be "upgraded" to the paid version of a course, which includes instructor's feedback and grades for the submitted assignments, and (if the student gets a passing grade) a certificate of completion. [57] [60] Other Coursera courses, projects, specializations, etc. cannot be audited—they are only available in paid versions.

  6. Apache HBase - Wikipedia

    en.wikipedia.org/wiki/Apache_HBase

    HBase is an open-source non-relational distributed database modeled after Google's Bigtable and written in Java.It is developed as part of Apache Software Foundation's Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System) or Alluxio, providing Bigtable-like capabilities for Hadoop.

  7. Apache Spark - Wikipedia

    en.wikipedia.org/wiki/Apache_Spark

    Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...

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