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NumPy Training

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What is NumPy in Python?

NumPy is an open source library available in Python, which helps in mathematical, scientific, engineering, and data science programming. It is a very useful library to perform mathematical and statistical operations in Python. It works perfectly for multi-dimensional arrays and matrix multiplication. It is easy to integrate with C/C++ and Fortran.

For any scientific project, NumPy is the tool to know. It has been built to work with the N-dimensional array, linear algebra, random number, Fourier transform, etc.

Syllabus of TensorFlow Training

Module 1: Introduction
  • Lesson 1 - Introduction to Numpy
  • Lesson 2 - Python NumPy
  • Lesson 3 - NumPy array in Python
  • Lesson 4 - Basics of NumPy Arrays
  • Lesson 5 - Python Lists VS Numpy Arrays
  • Lesson 6 - Numpy – ndarray
  • Lesson 7 - Data type Object (dtype) in NumPy Python
Module 2: Creating NumPy Array
  • Lesson 1 - Numpy – Array Creation
  • Lesson 2 - The Arange Method
  • Lesson 3 - The Zero Method
  • Lesson 4 - Create a Numpy array filled with all ones
  • Lesson 5 - The linspace Method
  • Lesson 6 - The eye Method
  • Lesson 7 - Numpy Meshgrid function
  • Lesson 8 - Creating a one-dimensional NumPy array
  • Lesson 9 - How to create an empty and a full NumPy array?
  • Lesson 10 - Create a Numpy array filled with all zeros
  • Lesson 11 - Create a Numpy array filled with all ones
  • Lesson 12 - How to generate 2-D Gaussian array using NumPy?
  • Lesson 13 - How to create a vector in Python using NumPy
  • Lesson 14 - Create the record array from list of individual records
Module 3: NumPy Array Manipulation
  • Lesson 1 - Copy and View in NumPy Array
  • Lesson 2 - How to Copy NumPy array into another array?
  • Lesson 3 - Appending values at the end of an NumPy array
  • Lesson 4 - How to swap columns of a given NumPy array?
  • Lesson 5 - Insert a new axis within a NumPy array
  • Lesson 6 - Stack the sequence of NumPy array horizontally
  • Lesson 7 - Stack the sequence of NumPy array vertically
  • Lesson 8 - Joining NumPy Array
  • Lesson 9 - Combining a one and a two-dimensional NumPy Array
  • Lesson 10 - Concatenate two arrays – np.ma.concatenate()
  • Lesson 11 - Combined array index by index
  • Lesson 12 - Splitting Arrays in NumPy
  • Lesson 13 - Compare two NumPy arrays
  • Lesson 14 - Find the union of two NumPy arrays
  • Lesson 15 - Find unique rows in a NumPy array
  • Lesson 16 - Get the unique values from an array
  • Lesson 17 - Trim the leading and/or trailing zeros from a 1-D array
Module 4: Matrix in NumPy
  • Lesson 1 - Matrix manipulation in Python
  • Lesson 2 - numpy matrix operations | empty() function
  • Lesson 3 - numpy matrix operations | zeros() function
  • Lesson 4 - numpy matrix operations | ones() function
  • Lesson 5 - numpy matrix operations | eye() function
  • Lesson 6 - numpy matrix operations | identity() function
  • Lesson 7 - Adding and Subtracting Matrices in Python
  • Lesson 8 - Matrix Multiplication in NumPy
  • Lesson 9 - Dot product of two arrays
  • Lesson 10 - NumPy | Vector Multiplication
  • Lesson 11 - How to calculate dot product of two vectors in Python?
  • Lesson 12 - Multiplication of two Matrices in Single line using Numpy in Python
  • Lesson 13 - Get the eigen values of a matrix
  • Lesson 14 - Calculate the determinant of a matrix using NumPy
  • Lesson 15 - Find the transpose of the matrix
  • Lesson 16 - Find the variance of a matrix
  • Lesson 17 - Compute the inverse of a matrix using NumPy
Module 5: Operations on NumPy Array
  • Lesson 1 - Numpy – Binary Operations
  • Lesson 2 - Numpy – Mathematical Function
  • Lesson 3 - Numpy – String Operations
Module 6: Reshaping NumPy Array
  • Lesson 1 - Reshape NumPy Array
  • Lesson 2 - Resize the shape of the given matrix
  • Lesson 3 - Reshape the shape of the given matrix
  • Lesson 4 - Get the Shape of NumPy Array
  • Lesson 5 - Change the dimension of a NumPy array
  • Lesson 6 - Change shape and size of array in-place
  • Lesson 7 - Flatten a Matrix in Python using NumPy
  • Lesson 8 - Flatten a matrix – matrix.ravel()
  • Lesson 9 - Move axes of an array to new positions
  • Lesson 10 - Interchange two axes of an array
  • Lesson 11 - Swap the axes a matrix
  • Lesson 12 - Split an array into multiple sub-arrays vertically
  • Lesson 13 - Split an array into multiple sub-arrays horizontally
  • Lesson 14 - Give a new shape to the masked array without changing its data
  • Lesson 15 - Squeeze the size of a matrix
Module 7: Indexing NumPy Array
  • Lesson 1 - Basic Slicing and Advanced Indexing in NumPy Python
  • Lesson 2 - Get selected slices of an array along mentioned axis
  • Lesson 3 - Accessing Data Along Multiple Dimensions Arrays in Python Numpy
  • Lesson 4 - How to access different rows of a multidimensional NumPy array?
  • Lesson 5 - Get the indices for the lower-triangle of an (n, m) array
Module 8: Arithmetic operations on NumPy Array
  • Lesson 1 - Broadcasting with NumPy Arrays
  • Lesson 2 - Estimation of Variable
  • Lesson 3 - Python: Operations on Numpy Arrays
  • Lesson 4 - How to use the NumPy sum function?
  • Lesson 5 - Divide the NumPy array element wise
  • Lesson 6 - Computes the inner product of two arrays
  • Lesson 7 - Absolute Deviation and Absolute Mean Deviation using NumPy
  • Lesson 8 - Find the standard deviation a matrix
  • Lesson 9 - Calculate the GCD of the NumPy array
Module 9: Linear Algebra in NumPy Array
  • Lesson 1 - Numpy | Linear Algebra
  • Lesson 2 - Get the QR factorization of a given NumPy array
  • Lesson 3 - How to get the magnitude of a vector in NumPy?
  • Lesson 4 - Compute the eigenvalues and right eigenvectors of a given square array using NumPy?
Module 10: NumPy and Random Data
  • Lesson 1 - Random sampling in numpy | ranf() function
  • Lesson 2 - Random sampling in numpy | random() function
  • Lesson 3 - Random sampling in numpy | random_sample() function
  • Lesson 4 - Random sampling in numpy | sample() function
  • Lesson 5 - Random sampling in numpy | random_integers() function
  • Lesson 6 - Random sampling in numpy | randint() function
  • Lesson 7 - Get random elements from NumPy – random.choice()
  • Lesson 8 - How to choose elements from the list with different probability using NumPy?
  • Lesson 9 - How to get weighted random choice in Python?
  • Lesson 10 - How to get the random positioning of different integer values?
  • Lesson 11 - Get Random Elements form geometric distribution
  • Lesson 12 - Get Random samples of a sequence of permutation
Module 11: Sorting and Searching in NumPy Array
  • Lesson 1 - Searching in a NumPy array
  • Lesson 2 - How to sort a Numpy Array
  • Lesson 3 - Numpy – Sorting, Searching and Counting
  • Lesson 4 - Variations in different Sorting techniques in Python
  • Lesson 5 - Sort a complex array
  • Lesson 6 - Get the minimum value of masked array
  • Lesson 7 - Sort the values in a matrix
  • Lesson 8 - Sort the elements in the given matrix having one or more dimension
Module 12: Universal Functions
  • Lesson 1 - Numpy ufunc | Universal functions
  • Lesson 2 - Create your own universal function in NumPy
Module 13: Working With Images
  • Lesson 1 - Create a white image using NumPy in Python
  • Lesson 2 - Convert a NumPy array to an image
  • Lesson 3 - How to Convert images to NumPy array?
  • Lesson 4 - Convert an image to NumPy array and save it to CSV file using Python?
Module 14: Projects and Applications with NumPy
  • Lesson 1 - Print checkerboard pattern of nxn using numpy
  • Lesson 2 - Implementation of neural network from scratch using NumPy
  • Lesson 3 - Analyzing selling price of used cars using Python
Module 14: Python Numpy Exercises
  • Lesson 1 - Python NumPy – Practice Exercises, Questions, and Solutions
  • Lesson 2 - Python MCQ (Multiple Choice Questions) with Answers
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Summary NumPy

👉 Python is an open source library available in Python, which helps in mathematical, scientific, engineering, and data science programming.

👉 numpy.zeros() or np.zeros Python function is used to create a matrix full of zeroes.

👉 numpy.ones() in Python can be used when you initialize the weights during the first iteration in TensorFlow and other statistic tasks.

👉 Python NumPy Reshape function is used to shape an array without changing its data.

👉 Python NumPy Flatten function is used to return a copy of the array in one-dimension.

👉 Numpy.hstack is a function in Python that is used to horizontally stack sequences of input arrays in order to make a single array.

👉 Numpy.vstack is a function in Python which is used to vertically stack sequences of input arrays in order to make a single array.

👉 numpy.arange() is an inbuilt numpy function that returns an ndarray object containing evenly spaced values within a defined interval.

👉 Numpy.dot product is a powerful library for matrix computation.

👉 The Numpy matmul() function is used to return the matrix product of 2 arrays.

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