regression. These exercises have been extensively tested with Matlab, but they should also work in Octave, which has been called a “free version of Matlab”. If you are using Octave, be sure to install the Image using gradient descent algorithm, based on which, we can predict the height given a new age value. In Matlab/Octave, you can load the training set using the commands x = load ( ’ ex1x . dat ’ ) ; y = load starting gradient descent, we need to add the x0 = 1 intercept term to every example. To do this in Matlab/Octave, the command is m = length (y ) ; % st or e the number of t r a i n i n g examples x = [

the number of colors it contains. To begin, download data6.zip and unpack its contents into your Matlab/Octave working directory. Photo credit: The bird photo used in this exercise belongs to Frank Wouters you will then use the 16 colors to replace the pixels in the large image. 3 K-means in Matlab/Octave In Matlab/Octave, load the small image into your program with the following command: A = double (

someone or something? . . . . . . . . . . . . . . . . . . . . . . . . . . . 411 Why don't you compile Matlab/Python/R/… code to Julia? . . . . . . . . . . . . . . . . . . . . . 411 37.2 Sessions and the REPL . . . 428 38 Noteworthy Differences from other Languages 429 38.1 Noteworthy differences from MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 38.2 Noteworthy differences from ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general program- ming. To achieve this, Julia builds upon the lineage

someone or something? . . . . . . . . . . . . . . . . . . . . . . . . . . . 413 Why don't you compile Matlab/Python/R/… code to Julia? . . . . . . . . . . . . . . . . . . . . . 413 37.2 Sessions and the REPL . . . 430 38 Noteworthy Differences from other Languages 431 38.1 Noteworthy differences from MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 38.2 Noteworthy differences from ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general program- ming. To achieve this, Julia builds upon the lineage

someone or something? . . . . . . . . . . . . . . . . . . . . . . . . . . . 411 Why don't you compile Matlab/Python/R/… code to Julia? . . . . . . . . . . . . . . . . . . . . . 411 37.2 Sessions and the REPL . . . 428 38 Noteworthy Differences from other Languages 429 38.1 Noteworthy differences from MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 38.2 Noteworthy differences from ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general program- ming. To achieve this, Julia builds upon the lineage

someone or something? . . . . . . . . . . . . . . . . . . . . . . . . . . . 411 Why don't you compile Matlab/Python/R/… code to Julia? . . . . . . . . . . . . . . . . . . . . . 411 37.2 Sessions and the REPL . . . 428 38 Noteworthy Differences from other Languages 429 38.1 Noteworthy differences from MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 38.2 Noteworthy differences from ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general program- ming. To achieve this, Julia builds upon the lineage

. . . 408 38 Noteworthy Differences from other Languages 410 38.1 Noteworthy differences from MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410 38.2 Noteworthy differences from ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general program- ming. To achieve this, Julia builds upon the lineage following languages, then you should start by reading the section on noteworthy differences from MATLAB, R, Python, C/C++ or Common Lisp. This will help you avoid some common pitfalls since Julia differs

. . . 408 38 Noteworthy Differences from other Languages 410 38.1 Noteworthy differences from MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410 38.2 Noteworthy differences from ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general program- ming. To achieve this, Julia builds upon the lineage following languages, then you should start by reading the section on noteworthy differences from MATLAB, R, Python, C/C++ or Common Lisp. This will help you avoid some common pitfalls since Julia differs

. . . 408 38 Noteworthy Differences from other Languages 410 38.1 Noteworthy differences from MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410 38.2 Noteworthy differences from ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general program- ming. To achieve this, Julia builds upon the lineage following languages, then you should start by reading the section on noteworthy differences from MATLAB, R, Python, C/C++ or Common Lisp. This will help you avoid some common pitfalls since Julia differs

. . . 408 38 Noteworthy Differences from other Languages 410 38.1 Noteworthy differences from MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410 38.2 Noteworthy differences from ease and expressiveness for high-level numerical computing, in the same way as languages such as R, MATLAB, and Python, but also supports general program- ming. To achieve this, Julia builds upon the lineage following languages, then you should start by reading the section on noteworthy differences from MATLAB, R, Python, C/C++ or Common Lisp. This will help you avoid some common pitfalls since Julia differs