Jupyter for Data Science Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

ISBN: 1785880071

Category: Uncategorized

Tag: Database/SQL


Posted on 2018-08-26, by nokia241186.

Description




Jupyter for Data Science: Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter by Dan Toomey
English | 20 Oct. 2017 | ISBN: 1785880071 | 242 Pages | EPUB | 4.58 MB



Get the most out of your Jupyter notebook to complete the trickiest of tasks in Data Science
Learn all the tasks in the data science pipeline-from data acquisition to visualization-and implement them using Jupyter
Get ahead of the curve by mastering all the applications of Jupyter for data science with this unique and intuitive guide

Book Description:
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 is a comprehensive guide to getting started with data science using the popular Jupyter notebook.

If you are familiar with Jupyter notebook and want to learn how to use its capabilities to perform various data science tasks, this is the book for you! 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. You will also see how you can utilize Jupyter's features to share your documents and codes with your colleagues. The book also explains how Python 3, R, and Julia can be integrated with Jupyter for various data science tasks.

By the end of this book, you will comfortably leverage the power of Jupyter to perform various tasks in data science successfully.

What you will learn:
Understand why Jupyter notebooks are a perfect fit for your data science tasks
Perform scientific computing and data analysis tasks with Jupyter
Interpret and explore different kinds of data visually with charts, histograms, and more
Extend SQL's capabilities with Jupyter notebooks
Combine the power of R and Python 3 with Jupyter to create dynamic notebooks
Create interactive dashboards and dynamic presentations
Master the best coding practices and deploy your Jupyter notebooks efficiently

About the Author:
Dan Toomey has been developing applications for over 20 years. He has worked in a variety of industries and companies of all sizes, in roles from sole contributor to VP/CTO level. For the last 10 years or so, he has been contracting companies in the eastern Massachusetts area under Dan Toomey Software Corp. Dan has also written R for Data Science and Learning Jupyter with Packt Publishing.

Table of Contents:
Jupyter and Data Science
Working with Analytical Data on Jupyter
Data Visualization & Prediction
Data Mining & SQL queries
R with Jupyter
Data Wrangling
Jupyter Dashboards
Statistical Modeling
Machine Learning Using Jupyter
Optimizing Jupyter Notebooks
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