In this tutorial, you’ll learn how to use the NumPy stack() function to join NumPy arrays along various axes. NumPy is an essential Python library for anyone working with data in Python. The NumPy stack() function allows you to combine… Read More »NumPy Stack: Join NumPy Arrays Along Different Axes
In this tutorial, you’ll learn how to use the NumPy squeeze() function. The np.squeeze() function allows you to remove single-dimensional entries from an array’s shape. This allows you to better transform arrays that aren’t shaped in the way that makes… Read More »NumPy Squeeze: Removing Dimensionality from NumPy Arrays
In this tutorial, you’ll learn how normalize NumPy arrays, including multi-dimensional arrays. Normalization is an important skill for any data analyst or data scientist. Normalizing a vector means that its vector magnitude is equal to 1, as a unit vector.… Read More »How to Normalize NumPy Arrays
In this tutorial, you’ll learn how to use the NumPy repeat() function. The np.repeat() function is used to repeat arrays and provides significant opportunity to customize how the arrays are repeated. Being able to work with NumPy arrays is an… Read More »NumPy Repeat Function: Repeating NumPy Arrays
In this post, you’ll learn the difference between arrays and lists in Python. Both these data structures let you store data in Python and share many similar properties. However, they also let you do quite different things and knowing when… Read More »Difference Between Array and List in Python
The median absolute deviation (MAD), is a robust statistic of variability that measures the spread of a dataset. In this tutorial, you’ll learn how to use Python to calculate the median absolute deviation. By the end of this tutorial, you’ll… Read More »How to Calculate the Median Absolute Deviation in Python
In this tutorial, you’ll learn how to implement the sigmoid activation function in Python. Because the sigmoid function is an activation function in neural networks, it’s important to understand how to implement it in Python. You’ll also learn some of… Read More »Implementing the Sigmoid Function in Python
In this tutorial, you’ll learn how to use the powerful NumPy pad function to pad arrays and matrices in NumPy and Python. The function is a powerful method that is often used in deep learning, especially in developing convolutional neural… Read More »NumPy Pad: Using np.pad() to Pad Arrays and Matrices
In this tutorial, you’ll learn how to use the NumPy where() function to process or return elements based on a single condition or multiple conditions. The np.where() function is one of the most powerful functions available within NumPy. The function… Read More »NumPy where: Process Array Elements Conditionally
In this tutorial, you’ll learn how to use the NumPy argmax() function to find the index of the largest value in an array. The np.argmax() function can be used to find the maximum value across an array, as well as… Read More »np.argmax(): How to Use NumPy Argmax
In this tutorial, you’ll learn how to use the NumPy linspace function to create arrays of evenly spaced numbers. This can be incredibly helpful when you’re working with numerical applications. The NumPy linspace function allows you to create evenly spaced… Read More »NumPy linspace: Creating Evenly Spaced Arrays with np.linspace
In this tutorial, you’ll learn how to use the NumPy logspace function and how to use its different parameters. The np.logspace() function is used to return numbers that are evenly spaced on a log scale. The function allows you to… Read More »NumPy logspace: Understanding the np.logspace() Function
