One of the great things about living in modernity is the ease of access to information. Being able to have the world’s top experts consolidate years of learning into a book that often costs less than $30 is invaluable. As I was learning data science, I read as many books as I could to accelerate my understanding of the field. In this post, I’ll highlight three that stood out and which I continue to reference today.
Storytelling with Data by Cole Knaflic
I would consider Cole Knaflic a modern-day Tufte, thanks to her ability to offer actionable and helpful advice on creating visualizations that focus on communicating data insights. I reference her book a lot whenever I’m working on important presentations. One of the key takeaways from her book is learning to leverage pre-attentive attributes like size, color, and position which can be used strategically to draw attention. An obvious example is using color to signify change (typically red for bad, green for good, however, she recommends blue for good and orange for bad to accommodate color blind people).
Hands-on Machine Learning by Aurélien Géron
When I was first starting to learn machine learning, this was my go-to resource. Aurélien does a great job of distilling machine learning concepts into a way that is approachable for beginners. By the end of it, you’ll have a good grasp of both the sci-kit learn and TensorFlow libraries in Python.
Player Piano by Kurt Vonnegut
While this is more of a sci-fi book, I still consider Player Piano to be a thought-provoking piece of literature by the masterful Kurt Vonnegut. In it, he explores the relationship of humanity to machines as they slowly get displaced and made irrelevant. As data scientists that develop machine learning algorithms that have the potential to displace workers, it’s important to think about the social ramifications of the work that we do.
People are finding that, because of the way the machines are changing the world, more and more of their old values don’t apply anymore. People have no choice but to become second-rate machines themselves, or wards of the machines. - Kurt Vonnegut