mcleonard

import numpy as np

def softmax(x, axis=0):
    """ Calculate softmax function for an array x
    
        axis=0 calculates softmax across rows which means each column sums to 1 
        axis=1 calculates softmax across columns which means each row sums to 1
    """
    return np.exp(x) / np.expand_dims(np.sum(np.exp(x), axis=axis), axis)

mcleonard

import ReactMarkdown from 'react-markdown';
import MathJax from 'react-mathjax';
import RemarkMathPlugin from 'remark-math';

function MarkdownRender(props) {
    const newProps = {
        ...props,
        plugins: [
          RemarkMathPlugin,
        ],

mcleonard

seq = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])

###
## For get_batches(seq, 2, 2)
# batch 1
x = array([[1, 2],
           [7, 8]]), 
y = array([[2, 3],
           [8, 9]]))

mcleonard

#!/bin/bash

FILE=$1
FILENAME="${FILE%%.*}"
FILE_DIR="${FILENAME}_files"

if [ -d $FILE_DIR ]; then
	# When converting a notebook to markdown, all the images in the markdown file link to the files
	# folder created when converting. We need to replace the file folder with
	# the static images folder used by Pelican.

mcleonard

pip list --outdated | grep -Eo '^[^ ]+' | xargs pip install -U

mcleonard

import math

class Vector(object):
    def __init__(self, *args):
        """ Create a vector, example: v = Vector(1,2) """
        if len(args)==0: self.values = (0,0)
        else: self.values = args
        
    def norm(self):
        """ Returns the norm (length, magnitude) of the vector """