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def softmax(x):
    """Calculates the softmax for each row of the input x.

    Your code should work for a row vector and also for matrices of shape (n, m).

    Argument:
    x -- A numpy matrix of shape (n,m)

    Returns:
    s -- A numpy matrix equal to the softmax of x, of shape (n,m)

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def normalizeRows(x):
    """
    Implement a function that normalizes each row of the matrix x (to have unit length).
    
    Argument:
    x -- A numpy matrix of shape (n, m)
    
    Returns:
    x -- The normalized (by row) numpy matrix. You are allowed to modify x.
    """

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def image2vector(image):
    """
    Argument:
    image -- a numpy array of shape (length, height, depth)
    
    Returns:
    v -- a vector of shape (length*height*depth, 1)
    """
    
    v = image.reshape((image.shape[0] * image.shape[1] * image.shape[2], 1))

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def sigmoid_derivative(x):
    """
    Compute the gradient (also called the slope or derivative) of the sigmoid function with respect to its input x.
    You can store the output of the sigmoid function into variables and then use it to calculate the gradient.
    
    Arguments:
    x -- A scalar or numpy array

    Return:
    ds -- Your computed gradient.

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def sigmoid(x):
    """
    Compute the sigmoid of x

    Arguments:
    x -- A scalar or numpy array of any size

    Return:
    s -- sigmoid(x)
    """

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Using Git

Global Settings

Related Setup: https://gist.github.com/hofmannsven/6814278

Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/

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title	output
R Notebook	html_notebook

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title	output
R Notebook	html_notebook

library(data.table)
fread("A,B
1,2

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title	output
R Notebook	html_notebook

write.table(read.table(text = "
 CHR_A     BP_A          SNP_A  CHR_B         BP_B          SNP_B           R2 
 1    154834183      rs1218582      1    154794318      rs9970364    0.0929391 

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# One chunk - Linear Regression in R

Source: https://medium.com/dsnet/linear-regression-with-pytorch-3dde91d60b50

```{r}
# Force using local Python environment
if (.Platform$OS.type == "unix") {
  reticulate::use_python(python = file.path(script_path, "..", "conda", "bin",
                                            "python3"), require = TRUE)
} else if (.Platform$OS.type == "windows") {