The Applied Data Science Workshop – Second Edition

eBook Details:

• Paperback: 352 pages
• Publisher: WOW! eBook (July 22, 2020)
• Language: English
• ISBN-10: 1800202504
• ISBN-13: 978-1800202504

eBook Description:

The Applied Data Science Workshop, 2nd Edition: Designed with beginners in mind, this workshop helps you make the most of Python libraries and the Jupyter Notebook’s functionality to understand how data science can be applied to solve real-world data problems

From banking and manufacturing through to education and entertainment, using data science for business has revolutionized almost every sector in the modern world. It has an important role to play in everything from app development to network security.

Taking an interactive approach to learning the fundamentals, this book is ideal for beginners. You’ll learn all the best practices and techniques for applying data science in the context of real-world scenarios and examples.

Starting with an introduction to data science and machine learning, you’ll start by getting to grips with Jupyter functionality and features. You’ll use Python libraries like scikit-learn, pandas, Matplotlib, and Seaborn to perform data analysis and data preprocessing on real-world datasets from within your own Jupyter environment. Progressing through the chapters, you’ll train classification models using sci-kit learn, and assess model performance using advanced validation techniques. Towards the end, you’ll use Jupyter Notebooks to document your research, build stakeholder reports, and even analyze web performance data.

• Understand the key opportunities and challenges in data science
• Use Jupyter for data science tasks such as data analysis and modeling
• Run exploratory data analysis within a Jupyter Notebook
• Visualize data with pairwise scatter plots and segmented distribution
• Assess model performance with advanced validation techniques
• Parse HTML responses and analyze HTTP requests

By the end of The Applied Data Science Workshop, Second Edition, you’ll be prepared to progress from being a beginner to taking your skills to the next level by confidently applying data science techniques and tools to real-world projects.