Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new,actionable insights from your data
Authors: Alex Galea
ISBN-10: 1789958172
ISBN-13: 9781789958171
Released: 2018-10-31
Print Length 页数: 192 pages
Book Description
Become the master player of data exploration by creating reproducible data processing pipelines,visualizations,and prediction models for your applications.
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.
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
contents
1 Jupyter Fundamentals
2 Data Cleaning and Advanced Machine Learning
3 Web Scraping and Interactive Visualizations
