NumPy is one of the fundamental packages for scientific computing with Python. The library is known for its dynamic features, such as numerical computing tools, support for a wide range of hardware and computing platforms, the flexibility of Python with the speed of compiled code, high-level syntax and more. NumPy is a must-have Python library in a data scientist’s toolkit.
Here are the ten best online resources to learn NumPy.
(The list is in no particular order)
1| NumPy Official Document
About: NumPy offers a comprehensive document, where it explains what this library is and how it works. The official document will help you learn NumPy from scratch. The topics included are NumPy basics, NumPy for MATLAB users, using NumPy C-API, nuts and bolts for developers, etc.
Know more here.
2| The Complete NumPy Course For Data Science: Hands-on NumPy
About: This course introduces most of the NumPy concepts. The course deals with what NumPy is, NumPy installation, creating NumPy array, mathematical & statistical functions, practical application on images, converting RGB to Grayscale to Binarize image with NumPy, applying average and edge detection filter on images, applying OneHot encoding technique with Basic NumPy functions etc.
Know more here.
3| Python NumPy Tutorial – Learn NumPy Arrays With Examples
About: In this Python NumPy tutorial, you will understand each aspect of Numpy, including what multidimensional NumPy arrays are, where NumPy is used, NumPy Arrays v/s List, why NumPy is used in Python, NumPy special functions etc. The examples provided in this tutorial make a case for why you should go for a Python Numpy array rather than a list.
Know more here.
4| Python NumPy Tutorial (with Jupyter and Colab)
About: This tutorial, offered by Stanford University, serves as a quick crash course on the Python programming language, NumPy library and its use for scientific computing. You will learn about arrays, array indexing, data types, array math, broadcasting and more.
Know more here.
5| Python NumPy For Absolute Beginners
About: This course offers in-depth yet simplified explanations for the fundamental concepts of Python NumPy. The course is meant for aspirants who want to learn the library’s fundamentals for data science and solve real-world problems. The topics covered include using Python interactively and using a Script, how to use the library for machine learning and data science, etc. You will also learn how to work with powerful tools in the NumPy array and get started with data exploration.
Know more here.
6| Guide to NumPy by Travis E. Oliphant
About: This is an e-book written by Travis E. Oliphant. The central purpose is to describe and document the basic NumPy system available under the NumPy namespace. The book provides a very detailed description of all the functions of NumPy and how it works. The topics covered in this book include object essentials, array object, basic routines, scalar objects, standard classes, data-type objects, universal functions etc.
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7| NumPy Tutorial – Everything You Need to Know to Get Started
About: This tutorial gives a simple introduction to Python’s NumPy library. You will gain a basic understanding of the most important NumPy functionality. This online tutorial contains a NumPy cheat sheet, limitations of NumPy, linear basics algebra, arrays and matrices, indexing and slicing.
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8| NumPy Data Science Essential Training
About: Through this course, offered by LinkedIn Learning, you will learn how to work with NumPy and Python within Jupyter Notebook. You will learn how to create NumPy arrays, use NumPy statements and snippets, and index, slice, iterate, and otherwise manipulate arrays. You will also learn how to plot data and combine NumPy arrays with Python classes and get examples of NumPy in action: solving linear equations, finding patterns, performing statistics, generating magic cubes, and more.
Know more here.
9| Python for Data Analysis: Pandas & NumPy
About: This is a hands-on course for beginners, available on Coursera, where you will understand Python programming fundamentals for data analysis, how to define single and multidimensional NumPy arrays as well as import HTML data in Pandas DataFrames.
Know more here.
10| NumPy For Data Science & Machine Learning
About: Through this online tutorial, you will learn about the fastest Python-based numerical multidimensional data processing framework. The topics cover what NumPy is, NumPy basics, indexing, file handling, Boolean arrays and sorting.
Know more here.
