Welcome to the #datamustread Book Club, a community of data-minded individuals who share a passion for reading and learning. You might be wondering, why a book club for data enthusiasts? Well, there are several reasons.
First, as someone who loves books and data, I could never find a book club that catered to both interests. So I decided to start one myself!
Second, based on my recent experiments, I’ve found that I can significantly increase an author’s print sales by marketing their audio and e-books. As someone who loves helping great authors succeed, this is an exciting opportunity for me to showcase some of the best books on data and analytics.
But perhaps most importantly, the community on this blog is incredible. We’re a group of like-minded people who love to discuss and share insights on all things data. And what better way to do that than to read and discuss books together? Imagine thousands of people reading the same book every month, interacting with each other and the author, and sharing their thoughts and ideas. It’s an exciting prospect, and I can’t wait to see where this book club takes us. So join us and let’s dive into some amazing books together!
Nachdem ich bereits Erfahrung als Buchautor (hier und hier) gesammelt habe, hatte ich kürzlich die Gelegenheit als Technical Reviewer ein sehr spannendes Buchprojekt zu unterstützen. Das Buch Machine Learning kompakt: Alles, was Sie wissen müssen, geschrieben von Andriy Burkov, fand ich dabei dermaßen interessant, dass ich es gerne im Folgenden kurz vorstellen werde:
Machine Learning kompakt von Andriy Burkov ist ein hervorragend geschriebenes Buch und ein Muss für jeden, der sich für Machine Learning interessiert.
Andriy Burkov gelang ein ausgewogenes Verhältnis zwischen der Mathematik, intuitiven Darstellungen und verständlichen Erklärungen zu finden. Dieses Buch wird Neulingen auf dem Gebiet als gründliche Einführung zu Machine Learning zugutekommen. Darüber hinaus dient das Buch Entwicklern als perfekte Ergänzung zu Code-intensiver Literatur, da hier die zugrunde liegenden Konzepte beleuchtet werden.
Machine Learning kompakt eignet sich außerdem als Lehrbuch für einen allgemeinen Kurs zu Machine Learning. Ich wünschte, ein solches Buch gäbe es, als ich studiert habe!
Protip: viele der im Buch vorgestellten Machine-Learning-Algorithmen können Sie einfach und bequem in Microsoft Azure Machine Learning Studio selbst ausprobieren: https://aka.ms/mlst
Today, data is at the core of everything we do, but the journey to mastering it can be overwhelming. Last year I started lecturing a Data Analytics course at university (as part of an MBA program). In the meanwhile, I was refining the list of books that I highly recommend to read. Three of these books form the Data Journey!
The Data Journey: A Human-Focused Approach to Data Storytelling
The Data Journey is not just about numbers; it’s about understanding the evolution of data, the power of visualization, and how it all connects to real-world business. Here are the books that will guide you on this path:
1. Info We Trust: How to Inspire the World with Data
Begin your Data Journey with a deep dive into data storytelling. Info We Trust explores data lifecycle across disciplines, with inspiring references and hand-drawn illustrations. It’s a must-read for anyone serious about data communication.
This book examines all parts of the data storytelling lifecycle across disciplines. The use of marginalia and hand-drawn illustrations give you both simple lessons to take away and insights into where to find out more. The book is full of magnificent references that inspire further reading.
2. Visual Analytics with Tableau
Ready for hands-on experience? My book, Visual Analytics with Tableau, provides a step-by-step guide to mastering Tableau, from basic chart creation to advanced statistical modeling. With Tableau available for free to students, there’s no reason not to dive in!
Visual Analytics with Tableau covers everything you need to get started with Tableau (students get Tableau for free!). The book guides you from the first steps of connecting to data, creating different types of charts, and adding calculation fields to more advanced features such as table calculations, forecasts, and clusters, as well as R, Python, and MATLAB integration for sophisticated statistical modeling.
3. The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios
Back to business (as this course is designed for an MBA program). We close our Data Journey canon with The Big Book of Dashboards. This is a comprehensive reference book with real-world solutions for business dashboards and a detailed analysis of do’s and don’ts.
This comprehensive reference book offers real-world solutions for business dashboards. It’s a practical guide to understanding do’s and don’ts in data visualization, categorized by industry and functional business areas.
Need More Inspiration for Mastering Data Journey? #MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time
Because vizzing alone is only half the fun, you should not miss the #MakeoverMonday book. Eva Murray and Andy Kriebel are icons in the data visualization community (read the interview!) and they have curated the thousands of visualizations from the #MakeoverMonday project into a practical guide that will take your design and data communication skills to the next level!
The #MakeoverMonday book by Eva Murray and Andy Kriebel is a treasure trove of data visualization insights. It’s a practical guide to enhancing your design and communication skills.
Join the Conversation: Your Recommendations for the #DataJourney
Interested in more insights on data visualization, analytics, and Tableau? Follow me on Twitter and LinkedIn, and let’s continue learning together. And don’t forget to check out my book Visual Analytics with Tableau to take your data journey to the next level!
What other books have inspired you on your data journey? Share your favorite data books in the blog post comments or reply to this tweet:
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