Tag: Python
Creating an array filled with ones in Python NumPy : np.ones
NumPy’s np.ones is a function used to create a NumPy array filled with ones. Similar to np.zeros, this function is…
Creating an array filled with zeros in Python NumPy : np.zeros
NumPy’s np.zeros is a function used to create a NumPy array filled with zeros. This function is particularly useful when…
NumPy Arrays : Understanding and using NumPy arrays with real-world examples
NumPy, short for “Numerical Python,” is a fundamental library for scientific computing in Python. One of its core features is…
Python Script: Extracting email addresses from a text file
In this article, we’ll guide you through the process of creating a Python script for this purpose, explain each part…
Handling NULL values in dynamic SQL insert statements using Python
In this we are dynamically creating and executing SQL insert statements to add rows from a DataFrame to a Snowflake…
Convolutional Neural Network – keras activation function options other than relu
In a Convolutional Neural Network (CNN), the activation function introduces non-linearity into the model, allowing it to learn from the…
Getting total number of elements in a NumPy array using Python NumPy’s np.ndarray.size
In NumPy, np.ndarray.size is an attribute that provides information about the total number of elements in a NumPy array. It…
Dividing an array vertically along rows, creating multiple smaller arrays using NumPy’s np.vsplit
np.vsplit is one such function that allows you to divide an array vertically along rows, creating multiple smaller arrays. It…
Dividing an array horizontally along columns, creating multiple smaller arrays using Python NumPy’s np.hsplit
np.hsplit is one such function that allows you to divide an array horizontally along columns, creating multiple smaller arrays. It…
Stacking arrays along a new axis, providing a powerful way to combine arrays using Python NumPy’s np.stack
np.stack is one such function that allows you to stack arrays along a new axis, providing a powerful way to…
