Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new, actionable insights from your data

Galea

$9.99 ~~$25.99~~

4.3 (3 Ratings)

eBook Oct 2018 192 pages 1st Edition

Galea

$9.99 ~~$25.99~~

4.3 (3 Ratings)

eBook Oct 2018 192 pages 1st Edition

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Key benefits

Get up and running with the Jupyter ecosystem and some example datasets
Learn about key machine learning concepts such as SVM, KNN classifiers, and Random Forests
Discover how you can use web scraping to gather and parse your own bespoke datasets

Description

Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations.

Who is this book for?

Applied Data Science with Python and Jupyter is ideal for professionals with a variety of job descriptions across a large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries such as Pandas, Matplotlib, and Pandas providing you a useful head start.

What you will learn

Get up and running with the Jupyter ecosystem
Identify potential areas of investigation and perform exploratory data analysis
Plan a machine learning classification strategy and train classification models
Use validation curves and dimensionality reduction to tune and enhance your models
Scrape tabular data from web pages and transform it into Pandas DataFrames
Create interactive, web-friendly visualizations to clearly communicate your findings

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Lukas K. Aug 09, 2019

Although this book only covers some of the techniques and approaches usually encountered when reading about data sciences, it covers them really well. And it has a clear structure. I especially liked the broad coverage on Jupyter at the beginning of the book. I can recommend this book to everyone that wants to get into the field of data science. You definitely, need some further material, but it certainly adds knowledge and value.

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wPastor Mar 01, 2019

The iBook version contain blurred images for that reason I bought the paper version.The book is perfect for me as a new guy in data science. The author teachs how to install anaconda and how to uptodate it's libraries. Shows how to work with jupyter notebooks and analize libraries such as pandas, matplotlib, numpy, etc.Excellent book to learn how to clean up data and show the results you are looking for.

kia Feb 08, 2019

I just purchased the book online. Some of the code examples are so blurred that are unreadable

Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new, actionable insights from your data

What do you get with eBook?