NumPy & File Handling

Python’s beginner libraries to start Machine Learning.

Credit: Author

In this blog, we will look at Python modules(NumPY & File Handling) necessary for Machine Learning. Please try to run the code by yourself for a better understanding.

Prerequisite; Basic knowledge of Python is necessary to understand this blog.

NumPy: NumPY is a Python library used for working with arrays. It also has functions for working in domain of linear algebra, Fourier transform (Fourier Transform is an important image processing tool which is used to decompose an image into its sine and cosine components), and matrices.

NumPy aims to provide an array object that is up to 50x faster than traditional Python lists. The array object in NumPY is called, it provides a lot of supporting functions that make working with ndarray very easy. We will also go through few statistics using the NumPy library.

NOTE : In Python, we read images as NumPY arrays, which you will see in further blogs of deep learning.

File Handling in Python: File handling is an important part of any web application. Python has several functions for creating, reading, updating, and deleting files.

In Data Science we mostly deal with CSV(Comma Separated Values) form of files. We mostly use pandas for opening this CSV form of file and creating a data frame. We will mostly discuss pandas while learning the core Data Science in further blogs.

For further reference, refer to the doc.

Learning and exploring this beautiful world with amazing tech.