Dive into a comprehensive 60-minute crash course on NumPy, the core library for scientific computing in Python. Master essential functions, tricks, and useful methods crucial for data science and machine learning algorithms. Explore topics including NumPy basics, array operations, multidimensional arrays, indexing techniques, reshaping, concatenation, broadcasting, functions and axis manipulation, datatypes, array generation, random number generation, linear algebra operations, and CSV file loading. Gain hands-on experience with provided code examples and enhance your Python skills for scientific computing and data analysis.
Overview
Syllabus
- Overview
- NumPy Introduction
- Installation and Basics
- Array vs List
- Dot Product
- Speed Test array vs list
- Multidimensional nd arrays
- Indexing/Slicing/Boolean Indexing
- Reshaping
- Concatenation
- Broadcasting
- Functions and Axis
- Datatypes
- Copying
- Generating arrays
- Random numbers
- Linear Algebra Eigenvalues / Solving Linear Systems
- Loading CSV files
Taught by
Python Engineer
