Studies

Books that I am Currently Reading

• Machine Learning Pocket Reference: Working with Structured Data in Python - Matt Harrison (**)

• Practical Time Series Analysis: Prediction with Statistics and Machine Learning - Aileen Nielsen (**)

• Fundamentals of Probability and Statistics (from Portuguese, Noções de Probabilidade e Estatística) - Marcos Nascimento Magalhães (**)

Books that I Read and Recommend

• Practical Statistics for Data Scientists - Peter Bruce, Andrew Bruce & Peter Gedeck (**)

• Designing Machine Learning Systems - Chip Huyen (**)

• Clean Code - Robert C. Martin (**)

• The Hundred-Page Machine Learning Book - Andriy Burkov (**)

• Machine Learning with R - Brett Lantz (**)

• Dive Into Design Patterns - Alexander Shvets (**)

• The Pragmatic Programmer - David Thomas & Andrew Hunt (**)

• Distributed Systems - Maarten Van Steen & Andrew S Tanenbaum (**)

Reading Queue

• Designing Data-Intensive Applications - Martin Kleppmann (**)

• Machine Learning Engineering - Andriy Burkov (**)

• Clean Architecture - Robert C. Martin (**)

• Artificial Intelligence: A Modern Approach - Stuart Russel & Peter Norvig

• Inspired: How to Create Tech Products Customers Love - Marty Cagan (**)

• Fundamentals of Natural Computing - Leandro Nunes de Castro (**)

• The Art of Computer Programming - Donald E. Knuth (**)

Wish List

• Data Science on AWS - Chris Fregly & Antje Barth

• 99 Bottles of OOP - Sandi Metz

• Essential Math for Data Science - Thomas Nield

(**) Books that I own