Julia

Copyright
 Credits
 Preface
 Preface
 Table of Contents
 Module 1: Getting Started with Julia
 The Rationale for Julia
 The scope of Julia
 Julia's place among the other programming languages
 A comparison with other languages for the data scientist
 Useful links
 Summary
 Chapter 1: Installing the Julia Platform
 Installing Julia
 Working with Julia's shell
 Startup options and Julia scripts
 Packages
 Installing and working with Julia Studio
 Installing and working with IJulia
 Installing Sublime-IJulia
 Installing Juno
 Other editors and IDEs
 How Julia works
 Summary. Chapter 2: Variables, Types, and OperationsVariables, naming conventions, and comments
 Types
 Integers
 Floating point numbers
 Elementary mathematical functions and operations
 Rational and complex numbers
 Characters
 Strings
 Regular expressions
 Ranges and arrays
 Dates and times
 Scope and constants
 Summary
 Chapter 3: Functions
 Defining functions
 Optional and keyword arguments
 Anonymous functions
 First-class functions and closures
 Recursive functions
 Map, filter, and list comprehensions
 Generic functions and multiple dispatch
 Summary
 Chapter 4: Control Flow. Conditional evaluationRepeated evaluation
 Exception handling
 Scope revisited
 Tasks
 Summary
 Chapter 5: Collection Types
 Matrices
 Tuples
 Dictionaries
 Sets
 Example project --
word frequency
 Summary
 Chapter 6: More on Types, Methods, and Modules
 Type annotations and conversions
 The type hierarchy --
subtypes and supertypes
 User-defined and composite types
 Types and collections --
inner constructors
 Type unions
 Parametric types and methods
 Standard modules and paths
 Summary
 Chapter 7: Metaprogramming in Julia
 Expressions and symbols
 Eval and interpolation
 Defining macros. Built-in macrosReflection capabilities
 Summary
 Chapter 8: I/O, Networking, and Parallel Computing
 Basic input and output
 Working with files
 Using DataFrames
 Working with TCP sockets and servers
 Interacting with databases
 Parallel operations and computing
 Summary
 Chapter 9: Running External Programs
 Running shell commands
 Calling C and FORTRAN
 Calling Python
 Performance tips
 Summary
 Chapter 10: The Standard Library and Packages
 Digging deeper into the standard library
 Julia's package manager
 Publishing a package
 Graphics in Julia
 Using Gadfly on data
 Summary. Appendix: List of Macros and PackagesMacros
 List of packages
 Module 2: Julia High Performance
 Chapter 1: Julia is Fast
 Julia --
fast and dynamic
 Designed for speed
 How fast can Julia be?
 Summary
 Chapter 2: Analyzing Julia Performance
 Timing Julia code
 The Julia profiler
 Analyzing memory allocation
 Statistically accurate benchmarking
 Summary
 Chapter 3: Types in Julia
 The Julia type system
 Type-stability
 Kernel methods
 Types in storage locations
 Summary
 Chapter 4: Functions and Macros --
Structuring Julia Code for High Performance
 Using globals
 Inlining.