Libardo1

A new design for a radar chart in D3.js. You can read more about in on the blog I wrote "A different look for the D3 radar chart"

An older version of a radar chart that I adjusted two years ago when I was just starting to learn D3.js can be found here

Libardo1

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import os

def computeCost(X, y, theta):
    inner = np.power(((X * theta.T) - y), 2)
    return np.sum(inner) / (2 * len(X))

def gradientDescent(X, y, theta, alpha, iters):

Libardo1

import tensorflow as tf


tf.add(1, 2)
# 3

tf.sub(2, 1)
# 1

tf.mul(2, 2)

Libardo1

import tensorflow as tf

# create a constant 2X2 matrix
tensor_1 = tf.constant([[1., 2.], [3.,4]])

tensor_2 = tf.constant([[5.,6.],[7.,8.]])

# create a matrix multiplication operation
output_tensor = tf.matmul(tensor_1, tensor_2)

Libardo1

WITH monthly_usage AS (
    SELECT
      user_id,
      date_part('month', age(created_at, '1970-01-01')) +
      12 * date_part('year', age(created_at, '1970-01-01')) AS time_period
    FROM orders
    WHERE order_state = 'completed'
    GROUP BY 1, 2
    ORDER BY 1, 2)

Libardo1

Libardo1

import numpy as np
import cv2

# cv2.getGaborKernel(ksize, sigma, theta, lambda, gamma, psi, ktype)
# ksize - size of gabor filter (n, n)
# sigma - standard deviation of the gaussian function
# theta - orientation of the normal to the parallel stripes
# lambda - wavelength of the sunusoidal factor
# gamma - spatial aspect ratio
# psi - phase offset

Libardo1

Libardo1

"""Functions for downloading and reading MNIST data."""
from __future__ import print_function
import gzip
import os
import urllib
import numpy
SOURCE_URL = 'http://yann.lecun.com/exdb/mnist/'


def maybe_download(filename, work_directory):

Libardo1

import math

import Image
import Levenshtein


class BWImageCompare(object):
    """Compares two images (b/w)."""

    _pixel = 255