In less than 100 pages, Modeling Mindsets elucidates the worldviews behind various statistical modeling and machine learning mindsets.
"Modeling Mindsets offers a compact but informative overview over the different approaches, assumptions and goals when working with data. I strongly recommend gifting this book to your present and future colleagues to get the most out of your collaboration."
– Sebastian Raschka, Machine learning & AI researcher
Most books on modeling dive straight into the math and methodologies, leaving readers struggling to grasp the underlying assumptions and limitations. Written in a clear and concise style, Modeling Mindsets introduces approaches such as Bayesian inference, supervised learning, causal inference, and more.
With this book, you'll gain a deeper understanding of different modeling techniques, empowering you to choose the right one for your problem.
"It has taken me many years of fumbling around with ML and statistics to achieve a fraction of the intuition in the book. Save yourself the time!"
– Robert Martin
This book is for everyone who builds models from data: data scientists, statisticians, machine learners, and quantitative researchers. To get the most out of this book:
Don't read this book if:
Embrace the full potential of Modeling Mindsets by challenging your assumptions and being open to diverse perspectives.
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