NumPy for Beginners in Data Science

Almost Deep Learning ( Artificial Neural Networks ) is completely based on NumPy. Tensorflow, the most popular Deep Learning framework from Google uses Tensors as its basic data structure. Tensor is a specific form of NumPy arrays. Another popular deep learning framework Theano uses NumPy under the hood. Pytorch ( from Facebook ) is another deep learning library that uses Tensors as well.

Numpy is a python package specifically designed for efficiently working on homogeneous n–dimensional arrays . Since array level operations are highly mathematical in nature, most of numpy is written in C and wrapped with Python. This is the key to numpy s success.

This is how the Numpy Course is structured

NumPy Arrays – This is the core data structure in numpy. We will understand how to create arrays using lists and find out shape of arrays,

arange function – Similar to the range () function in Python, NumPy has a special function called arange () that creates a NumPy array. We will understand what makes it special and how to create it.

reshape function – Once arrays are created in NumPy, they might need to be reshaped. For example, a 6 x 2 array can be reshaped to a 3 x 4 or a 12 x 1. We will see how to do that