December 2016
Beginner
388 pages
8h 35m
English
Overview
If you've ever wondered how to bridge the gap between mathematics, programming, and actionable data insights, 'Principles of Data Science' is the guide for you. This book explores the full data science pipeline, providing you with tools and knowledge to transform raw data into impactful decisions. With practical lessons and hands-on tutorials, you'll master the essential skills of a data scientist.
What this Book will help me do
- Understand and apply the five core steps of the data science process.
- Gain insight into data cleaning, visualization, and effective communication of results.
- Learn and implement foundational machine learning models using Python or R.
- Bridge gaps between mathematics, statistics, and programming to solve data-driven problems.
- Evaluate machine learning models using key metrics for better predictive capabilities.
Author(s)
The author, a seasoned data scientist with years of professional experience in analytics and software development, brings a rich perspective to the topic. Combining a strong foundation in mathematics with expertise in Python and R, they have worked on diverse real-world data projects. Their teaching philosophy emphasizes clarity and practical application, ensuring you not only gain knowledge but also know how to apply it effectively.
Who is it for?
This book is intended for individuals with a basic understanding of algebra and some programming experience in Python or R. It is perfect for programmers who wish to dive into the world of data science or for those with math skills looking to apply them practically. If you seek to turn raw data into valuable insights and predictions, this book is tailored for you.
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