Packt+ | Advance your knowledge in tech

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Jupyter Cookbook

You're reading from Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

Product type Paperback

Published in Apr 2018

Publisher Packt

ISBN-13 9781788839440

Length 238 pages

Edition 1st Edition

Languages

JavaScript

Tools

Jupyter

Concepts

Data Analysis

Author (1):

Dan Toomey

View More author details

Table of Contents (12) Chapters

Preface

1. Installation and Setting up the Environment FREE CHAPTER

2. Adding an Engine

3. Accessing and Retrieving Data

4. Visualizing Your Analytics

5. Working with Widgets

6. Jupyter Dashboards

7. Sharing Your Code

8. Multiuser Jupyter

9. Interacting with Big Data

10. Jupyter Security

11. Jupyter Labs

Introduction

The Jupyter project has the specific objective of supplying a mechanism to reduce the gap between a user and their data. In this chapter, we will describe the wide range of possibilities of widgets in Jupyter. With these, we can include information for the user in a very good mood to show reporting of data in the same Jupiter tool. You will now make an interface like a human machine process; this will help you understand the basics of having programming software.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (1)

Toomey

Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.

See other products by Toomey

Other recommended products

Related to this chapter

Learning Jupyter 5

Learning Jupyter 5

In this book, you will learn how to build interactive dashboards in a Jupyter notebook. Explore JupyterHub and various Jupyter widgets through which you can easily perform 3D data visualization, 3D plotting, and geospatial analytics. This book helps you understand BeakerX to create interactive tables and interact with spreadsheets.

Aug 2018 9h 24m

Learning Jupyter 5

Learning Jupyter 5

In this book, you will learn how to build interactive dashboards in a Jupyter notebook. Explore JupyterHub and various Jupyter widgets through which you can easily perform 3D data visualization, 3D plotting, and geospatial analytics. This book helps you understand BeakerX to create interactive tables and interact with spreadsheets.

Aug 2018 9h 24m

JupyterLab Quick Start Guide

JupyterLab Quick Start Guide

Jupyterlab is a web-based data science interface and natural evolution of Jupyter Notebooks. This guide will take you through the core commands and functionalities of JupyterLab. You will learn to customize and enhance your JupyterLab productivity by installing additional extensions.

Dec 2019 5h 20m

Jupyter for Data Science

Jupyter for Data Science

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create documents that contain live code, equations and visualizations. This book will be a comprehensive guide to getting started with data science using the popular Jupyter notebook. It will show you how to leverage the capabilties of Jupyter to perform various data science tasks efficiently. From data exploration to visualization, this book will take you through every step of the way in implementing an effective data science pipeline using Jupyter.

Jupyter for Data Science

Jupyter for Data Science

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create documents that contain live code, equations and visualizations. This book will be a comprehensive guide to getting started with data science using the popular Jupyter notebook. It will show you how to leverage the capabilties of Jupyter to perform various data science tasks efficiently. From data exploration to visualization, this book will take you through every step of the way in implementing an effective data science pipeline using Jupyter.

Mastering Geospatial Analysis with Python

Mastering Geospatial Analysis with Python

Python comes with many libraries and tools that help you work on geoprocessing tasks without investing in expensive tools. This book introduces you to new libraries that perform geospatial and statistical analysis and data management. It uses examples that explain how Python v3 differs from v2, and solve age-old problems in geospatial analysis.

Apr 2018 14h 40m

Mastering Geospatial Analysis with Python

Mastering Geospatial Analysis with Python

Python comes with many libraries and tools that help you work on geoprocessing tasks without investing in expensive tools. This book introduces you to new libraries that perform geospatial and statistical analysis and data management. It uses examples that explain how Python v3 differs from v2, and solve age-old problems in geospatial analysis.

Apr 2018 14h 40m

Mastering Geospatial Analysis with Python

Mastering Geospatial Analysis with Python

Python comes with many libraries and tools that help you work on geoprocessing tasks without investing in expensive tools. This book introduces you to new libraries that perform geospatial and statistical analysis and data management. It uses examples that explain how Python v3 differs from v2, and solve age-old problems in geospatial analysis.

Apr 2018 14h 40m

Mastering Geospatial Analysis with Python

Mastering Geospatial Analysis with Python

Python comes with many libraries and tools that help you work on geoprocessing tasks without investing in expensive tools. This book introduces you to new libraries that perform geospatial and statistical analysis and data management. It uses examples that explain how Python v3 differs from v2, and solve age-old problems in geospatial analysis.

Apr 2018 14h 40m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m