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1
- Overview
2
- NumPy Introduction
3
- Installation and Basics
4
- Array vs List
5
- Dot Product
6
- Speed Test array vs list
7
- Multidimensional nd arrays
8
- Indexing/Slicing/Boolean Indexing
9
- Reshaping
10
- Concatenation
11
- Broadcasting
12
- Functions and Axis
13
- Datatypes
14
- Copying
15
- Generating arrays
16
- Random numbers
17
- Linear Algebra Eigenvalues / Solving Linear Systems
18
- Loading CSV files
Description:
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.

NumPy Crash Course - Complete Tutorial

Python Engineer
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