October 2018
Beginner
192 pages
3h 39m
English
Overview
Dive into the field of data science with "Applied Data Science with Python and Jupyter," a beginner-friendly guide designed to empower you with industry-relevant data analysis skills. In this book, you will learn the fundamentals of data workflows, get hands-on with machine learning basics, and explore interactive data visualization using Python and Jupyter.
What this Book will help me do
- Understand and utilize the Jupyter ecosystem for efficient data analysis.
- Conduct exploratory data analysis and clean data to prepare it for modeling.
- Build and train classification models using machine learning techniques.
- Scrape data from the web and process it into usable formats with Pandas.
- Develop compelling and interactive visualizations to present your insights effectively.
Author(s)
None Galea is an accomplished data scientist and software engineer with extensive experience in Python programming and data workflows. Passionate about teaching and sharing knowledge, they bring a practical and approachable style to their writing. None enjoys helping curious learners transition into data science by making complex topics accessible and actionable.
Who is it for?
The ideal reader for this book is someone with basic Python knowledge who is curious about data science and aims to acquire practical skills quickly. Professionals looking to integrate data science techniques into their workflows or individuals transitioning into a data science role will find this book invaluable. If you are familiar with libraries like Pandas or matplotlib, you'll feel right at home. Even if you have minimal Python experience, this book offers an excellent trajectory to learning data science.
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