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This is my story

This is my song.

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def insertion_sort(array)
  i = 0
  while i < array.length
    j = 0
    while array[j] < array[i]
      j += 1
    end
    
    # array[j] is the first element >= array[i]
    # delete array[i] and move it to just before position j

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#!/usr/bin/env bash

gcc -std=c11 -mavx -mavx2 convolution_test.c -o convolution_test

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import tensorflow as tf

# Notice that x and y have the same initial value, but y_var has
# totally different scale from x_var. Therefore y_var has much farther
# to change than x_var.
x_var = tf.Variable(1.0)
y_var = tf.Variable(100.0)
y_var_scaled = y_var / 100.0

# This is just a silly linear equation. It will have a derivative of 2

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import keras.backend as K
from keras.datasets import mnist
from keras.layers import Dense, Flatten, Input, Reshape
from keras.models import Model
from keras.optimizers import Adam
import numpy as np

# == This code trains a denoising autoencoder. ==
input_tensor = Input(shape = (28, 28))
flattened_input = Flatten()(input_tensor)

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# Resource: https://keras.io/getting-started/functional-api-guide/

import keras.backend as K
from keras.datasets import mnist
from keras.layers import Dense, Input, Lambda
from keras.models import Model
from keras.optimizers import Adam
from keras.utils import to_categorical
import numpy as np

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promise.then((result) => {
  // promise resolved successfully.
  console.log(`Result is ${result}`);
}, (error) => {
  // promise was failed
  console.log(`Error is ${error}`);
});

// Also: promise.then(null, (error) => { ... }) is the same as promise.catch((error) => { ... }).
// The Promise#catch method is just a convenience. You can always just pass a null success handler to then.

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from keras.datasets import imdb
import numpy as np

TOP_N_WORDS = 1_000
(x_train, y_train), (x_test, y_test) = imdb.load_data(
    num_words = TOP_N_WORDS
)

# Transform dataset from variable-length word sequences to a
# binary valued dense matrix.

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Heaps

Priority Queue

Heaps are an implementation of the priority queue abstract data type:

• insert(entry, priority).
  • priority is an integer priority. Entries with "higher priority" will be extracted before entries with "lower priority."
• Lower number often is "higher priority." This makes sense

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Binary Search Trees

---

Operations

• find
• insert
• delete
• Each has time complexity proportional to depth of the tree.