Fast Python aggressively rehashes the basics of Python programming in order to dispel myths and misconceptions about how to write fast code. Readers equipped with the lessons from this book will be able to test, diagnose, and optimize out performance bottlenecks in their own work. For each algorithm discussed, readers will walk through numerous progressively faster methods of programming it, all while picking up bits of fundamental knowledge about time complexity, memory efficiency, data structures, multi-threading, and vectorization. As such, this book is relevant to veterans looking refresh their methods and to computer science students navigating Algorithms 101. This book maintains a high standard of reproducibility. All of the graphics, tables, and code profiles contained in this book are fully reproducible and available to anyone in a public GitHub repository.
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Chris Conlan is the founder and CEO of Conlan Scientific, a financial data science consultancy based out of Charlotte, North Carolina. He works with his team of data scientists to build machine learning solutions for banks, lenders, investors, traders, and fintech companies. Chris graduated University of Virginia's College of Arts & Sciences with a degree in statistics, where he later co-taught a data science capstone course.
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