How did Spark become so efficient in data processing compared to MapReduce? Learn about Spark's powerful stack of libraries and big data processing functionalities.
Here we see the wrench that poorly implemented mutable values throws into your code. Learn about the symptoms and solutions you can use to fix the problem.
Learn about some of the tools you can use to help clients consume your API and create integrations by ensuring that it has informational documentation.
And no, we're not talking about Pavlov's dogs here. Learn about the reinforcement learning aspect of machine learning and the key algorithms that are involved!
Taking some inspiration from Python's argparse module, Argparse4j is a useful command-line argument parser library to consider when working with Python scripts.
Professor Ken Fogel defines the bean class, a subset of the original JavaBean concept, as a class used to aggregate or collect both primitive data types and other classes for modeling data in a program. He offers up examples and various rules for beans as they pertain to his courses.
Tablesaw is like an open-source Java power tool for data manipulation with hooks for interactive visualization, analytics, and machine learning. Come learn all about it!
