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Practical Machine Learning by Sunila Gollapudi

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Julia

Julia, in recent times, has gained much popularity and adoption in the Machine learning and data science fields as a high-performance alternative to Python. Julia is a dynamic programming language that is built to support distributed and parallel computing, thus known to be convenient and fast.

Performance in Julia is a result of the JIT compiler and type interfacing feature. Also, unlike other numeric programming languages, Julia does not enforce vectorization of values. Similar to R, MATLAB, and Python, Julia provides ease and expressiveness for high-level numerical computing.

Following are some key characteristics of Julia:

  • The core APIs and mathematical primitive operations are written in Julia
  • It consists rich types for constructing and ...

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