Python Numpy Data Analysis for Data Scientist | AI | ML | DL
Unlock the Power of Data Analysis with Python Pandas for Data Science, AI, Machine Learning, and Deep Learning
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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