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Numpy

Track :

Programming

Lessons no : 58

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What will you learn in this course?
  • Master array creation, manipulation, and indexing using NumPy for efficient data analysis and scientific computing
  • Perform complex mathematical operations, including linear algebra, Fourier transforms, and statistical analysis with NumPy
  • Utilize NumPy's broadcasting and vectorization features to optimize numerical computations in Python
  • Implement advanced array operations such as reshaping, stacking, and splitting for data preprocessing and analysis
  • Apply NumPy functions to perform element-wise calculations and aggregate data efficiently
  • Leverage NumPy's random module for generating random data and simulations in scientific research
  • Integrate NumPy with other data science libraries like Pandas and Matplotlib for comprehensive data analysis workflows
  • Use NumPy to handle large datasets and perform high-performance numerical computations in Python
  • Develop custom functions and algorithms utilizing NumPy's optimized array operations for real-world applications
  • Analyze and visualize data effectively by combining NumPy with visualization tools for insightful results
  • Solve linear algebra problems, including matrix multiplication, inversion, and eigenvalue computation using NumPy
  • Implement numerical methods and algorithms for scientific computing, data modeling, and machine learning tasks

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Lessons | 58
numpy print version
00:00:39

numpy print version
numpy create null vector
00:00:26

numpy create null vector
numpy print function doc
00:00:32

numpy print function doc
numpy create vector with value range
00:00:27

numpy create vector with value range
numpy reverse vector
00:00:31

numpy reverse vector
numpy create matrix with value range
00:00:27

numpy create matrix with value range
numpy get index of non zero elements
00:00:53

numpy get index of non zero elements
numpy create identity matrix
00:00:25

numpy create identity matrix
numpy create array with random values
00:00:25

numpy create array with random values
numpy create matrix with random values
00:00:30

numpy create matrix with random values
numpy matrix find min and max values
00:00:44

numpy matrix find min and max values
numpy vector find mean value
00:00:31

numpy vector find mean value
numpy array print number of dimensions
00:00:44

numpy array print number of dimensions
numpy create matrix of ones
00:00:24

numpy create matrix of ones
numpy create matrix of constant
00:00:26

numpy create matrix of constant
numpy create matrix patterns v1
00:00:31

numpy create matrix patterns v1
numpy create matrix patterns v2
00:00:32

numpy create matrix patterns v2
numpy create matrix patterns v3
00:00:40

numpy create matrix patterns v3
numpy create matrix patterns v4
00:00:42

numpy create matrix patterns v4
numpy create matrix patterns v5
00:00:48

numpy create matrix patterns v5
numpy print matrix inner matrix
00:00:34

numpy print matrix inner matrix
numpy rotate matrix left
00:00:52

numpy rotate matrix left
numpy rotate matrix right
00:00:50

numpy rotate matrix right
numpy create diagonal array
00:00:49

numpy create diagonal array
numpy get main diagonal from matrix
00:00:44

numpy get main diagonal from matrix
numpy get minor diagonal from matrix
00:00:33

numpy get minor diagonal from matrix
numpy create matrix pattern v6a
00:00:44

numpy create matrix pattern v6a
numpy create matrix pattern v6b
00:00:41

numpy create matrix pattern v6b
numpy linear to non linear index
00:00:35

numpy linear to non linear index
numpy non linear to linear index
00:00:35

numpy non linear to linear index
numpy matrix multiplication
00:01:07

numpy matrix multiplication
numpy negate array elements
00:00:50

numpy negate array elements
numpy round up float array
00:00:40

numpy round up float array
numpy round down float array
00:00:42

numpy round down float array
numpy create matrix with row values from 1 to 5
00:00:32

numpy create matrix with row values from 1 to 5
numpy create matrix with col values from 1 to 5
00:00:32

numpy create matrix with col values from 1 to 5
numpy transpose matrix
00:00:41

numpy transpose matrix
numpy transpose array
00:01:08

numpy transpose array
numpy append arrays
00:00:34

numpy append arrays
numpy matrix append array as row
00:00:47

numpy matrix append array as row
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NumPy can be used to perform a wide variety of mathematical operations on arrays. It adds powerful data structures to Python that guarantee efficient calculations with arrays and matrices and it supplies an enormous library .