Python Numpy Data Analysis for Data Scientist | AI | ML | DL

Python Numpy Data Analysis for Data Scientist | AI | ML | DL

What you’ll learn

  • Understand the basics of Numpy and how to set up the Numpy environment.
  • Create and access arrays, use indexing and slicing, and work with arrays of different dimensions.
  • Understand the ndarray object, data types, and conversion between data types.
  • Work with array attributes and different ways of creating arrays from existing data or ranges functions.
  • Apply broadcasting, iteration, and updating array values.
  • Perform array manipulation, joining, transposing, and splitting operations.
  • Apply string, mathematical, and trigonometric functions.
  • Perform arithmetic operations, including add, subtract, multiply, divide, floor_divide, power, mod, remainder, reciprocal, negative, and abs.
  • Apply statistical functions and counting functions.
  • Sort arrays using different methods, including sort(), argsort(), lexsort(), searchsorted(), partition(), and argpartition().
  • Understand the different types of array copies, including view, copy, “no copy”, shallow copy, and deep copy.

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