Book Image

Mastering Numerical Computing with NumPy

By : Umit Mert Cakmak, Tiago Antao, Mert Cuhadaroglu
Book Image

Mastering Numerical Computing with NumPy

By: Umit Mert Cakmak, Tiago Antao, Mert Cuhadaroglu

Overview of this book

NumPy is one of the most important scientific computing libraries available for Python. Mastering Numerical Computing with NumPy teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts. Beginning with NumPy's arrays and functions, you will familiarize yourself with linear algebra concepts to perform vector and matrix math operations. You will thoroughly understand and practice data processing, exploratory data analysis (EDA), and predictive modeling. You will then move on to working on practical examples which will teach you how to use NumPy statistics in order to explore US housing data and develop a predictive model using simple and multiple linear regression techniques. Once you have got to grips with the basics, you will explore unsupervised learning and clustering algorithms, followed by understanding how to write better NumPy code while keeping advanced considerations in mind. The book also demonstrates the use of different high-performance numerical computing libraries and their relationship with NumPy. You will study how to benchmark the performance of different configurations and choose the best for your system. By the end of this book, you will have become an expert in handling and performing complex data manipulations.
Table of Contents (11 chapters)

Configuring NumPy with low-level libraries using AWS EC2

  1. Log in to AWS. If you don't have an account, create one:
  1. Select EC2.
  1. Click Launch Instance:
  1. Select Ubuntu Server 16.04 LTS (HVM), SSD Volume Type - ami-db710fa3:

  1. Select the t2.micro instance type:
  1. Click Review and Launch:
  1. Click Launch.
  2. Select Create a new key pair:
  1. Give it a name and click Launch Instances. It will take a while for it to run:
  1. Once its status is running, click the Instance ID, which in this case is i-00ccaeca61a24e042. Then select the instance and click Connect:
  1. It will then show you the following window with some useful information:
  1. Open your terminal and navigate to the folder where you saved your generated key. The key name in this example is aws_oregon. Run the following command:
$ chmod 400 aws_oregon.pem
  1. Then, copy the line in the example section of the previous...