The Data Visualization Workshop, Second Edition
Döbler, Mario, Großmann, Tim
- 出版商: Packt Publishing
- 出版日期: 2020-02-27
- 售價: $1,170
- 貴賓價: 9.5 折 $1,112
- 語言: 英文
- 頁數: 480
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1838981489
- ISBN-13: 9781838981488
You already know you want to learn data visualization with Python, and a smarter way to learn is to learn by doing. The Data Visualization Workshop focuses on building up your practical skills so that you can develop clear, expressive real-world charts and diagrams. You'll learn from real examples that lead to real results.
Throughout The Data Visualization Workshop, you'll take an engaging step-by-step approach to understand data visualization with Python. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend learning how companies like Uber are using advanced visualization techniques to represent their data visually. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding.
Every physical print copy of The Data Visualization Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your book.
Fast-paced and direct, The Data Visualization Workshop is the ideal companion for Python beginners who want to get up and running with data visualization. You'll visualize your work like a skilled data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.
Mario Döbler is a Ph.D. student with a focus on deep learning at the University of Stuttgart. He previously interned at the Bosch Center for artificial intelligence in the Silicon Valley in the field of deep learning. He used state-of-the-art algorithms to develop cutting-edge products. In his master thesis, he dedicated himself to applying deep learning to medical data to drive medical applications.
Tim Großmann is a computer scientist with interest in diverse topics, ranging from AI and IoT to Security. He previously worked in the field of big data engineering at the Bosch Center for Artificial Intelligence in Silicon Valley. In addition to that, he worked on an Eclipse project for IoT device abstractions in Singapore. He's highly involved in several open-source projects and actively speaks at tech meetups and conferences about his projects and experiences.