Pedro L Ramos's books

All books Public 138 books (showing 31-45)

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Cover Title Author
Brian W Kernighan, Phillip J. Plauger: The Elements of Programming Style (1978, McGraw-Hill)The Elements of Programming Style,
Peter van der Linden: Expert C programming (1994)Expert C programming
Hadley Wickham, Garrett Grolemund: R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (2017, O'Reilly Media)R for Data Science: Import, Tidy, Transform, Visualize, and Model Data,
Marshall Kirk McKusick, George V. Neville-Neil: The Design and Implementation of the FreeBSD Operating System (2005, Addison-Wesley Professional)The Design and Implementation of the FreeBSD Operating System,
Dave Thomas: Programming Elixir: Functional |> Concurrent |> Pragmatic |> Fun (2014, Pragmatic Bookshelf)Programming Elixir: Functional |> Concurrent |> Pragmatic |> Fun
Luciano Ramalho, Luciano Ramalho: Fluent Python (Paperback, 2015, O’Reilly Media)Fluent Python,
Mark Richards, Neal Ford: Fundamentals of Software Architecture (Paperback, 2020, O'Reilly Media)Fundamentals of Software Architecture,
Harold Abelson, Gerald Jay Sussman: Structure and Interpretation of Computer Programs - 2nd Edition (1996)Structure and Interpretation of Computer Programs - 2nd Edition,
Andy Weir: Project Hail Mary (Hardcover, 2021, Ballantine Books)Project Hail Mary
Brendan Gregg: Systems Performance (2013, Prenctice-Hall)Systems Performance
Brendan Gregg: BPF Performance Tools (Paperback, 2019, Addison-Wesley Professional)BPF Performance Tools
José Rodrigues dos Santos: Fúria divina (Portuguese language, 2009, Gradiva)Fúria divina
Betsy Beyer, Chris Jones, Jennifer Petoff, Niall Richard Murphy: Site Reliability Engineering (2016, O'Reilly Media, Inc.)Site Reliability Engineering, , ,
Titus Winters, Tom Manshreck, Hyrum Wright: Software Engineering at Google (Paperback, 2020, O'Reilly Media)Software Engineering at Google, ,
No cover

Gareth James: An Introduction To Statistical Learning With Applications In R (2013, Springer-Verlag New York Inc.)

An Introduction To Statistical Learning With Applications In R