June 2018
Beginner
194 pages
4h 7m
English
Overview
Jumpstart your data science journey with 'Beginning Data Science with Python and Jupyter'. This book walks you through the rapidly growing field of Python-based data science, leading you from foundational concepts all the way to building actionable analyses. Through hands-on examples, you will master tools like Jupyter Notebook, key Python libraries, and practical machine learning techniques.
What this Book will help me do
- Gain proficiency with the Jupyter notebook ecosystem to effectively analyze and present data.
- Deep dive into crucial machine learning concepts and algorithms such as SVM and Random Forests.
- Learn to prepare and clean datasets, enhancing them for advanced data modeling.
- Employ web scraping to gather and format custom data directly from online sources.
- Create interactive visualizations to communicate your data-driven findings clearly to diverse audiences.
Author(s)
None Galea is a technologist with extensive experience in applying Python to data science workflows. Passionate about teaching, Galea focuses on simplifying complex technical concepts into approachable steps. Their method ensures learners not only grasp the tools but also understand applications in real-world scenarios.
Who is it for?
This book is ideal for aspiring data scientists or professionals across industries who seek to expand their data analysis skills. It is designed for readers with a working knowledge of Python, offering an accessible entry point into data science workflows. If you have tinkered with libraries like Pandas or Matplotlib, this book will hone your abilities. Begin your journey into insightful data exploration with this practical guide.
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