Book Image

IPython Interactive Computing and Visualization Cookbook

By : Fawaz Sammani
Book Image

IPython Interactive Computing and Visualization Cookbook

By: Fawaz Sammani

Overview of this book

Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. This course is equipped with several ready-to-use, focused recipes for high-performance scientific computing and data analysis to help you write better and faster code. You’ll be able to apply your learnings to various real-world examples, ranging from applied mathematics, scientific modeling, to machine learning. The course introduces you to effective programming techniques such as code quality and reproducibility, code optimization, and graphics card programming. You’ll also learn how to use different features of IPython and Jupyter Notebook in data science, signal and image processing, and applied mathematics. By the end of this course, you’ll learn how to easily analyze and visualize all types of data in Jupyter Notebook.
Table of Contents (11 chapters)
Chapter 5
Numerical Optimization
Content Locked
Section 3
Fitting a function to data with non-linear least squares
In this section, we will show an application of numerical optimization to nonlinear least squares curve fitting. The goal is to fit a function, depending on several parameters, to data points. In contrast to the linear least squares method, this function does not have to be linear in those parameters.