maxim5

#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = 'maxim'

import numpy as np


def kmeans_assignment(centroids, points):
  num_centroids, dim = centroids.shape
  num_points, _ = points.shape

maxim5

#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = 'maxim'

import tensorflow as tf
import numpy as np

def random_normal(shape):
  return (np.random.random(shape) - 0.5) * 2

maxim5

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import print_function

__author__ = 'maxim'

import sys
import numpy as np
import matplotlib.pyplot as plt

maxim5

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import print_function

__author__ = 'maxim'

import numpy as np
import gensim
import string

maxim5

import com.datastax.driver.core.Cluster;
import com.datastax.driver.core.ResultSet;
import com.datastax.driver.core.Row;
import com.datastax.driver.core.Session;

import java.util.List;

public class Main {
  public static void main(String[] args) {
    try {