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anantzoid /
Created Nov 23, 2016
Simple GAN implementation for MNIST data
import numpy as np
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
data = input_data.read_data_sets('/Users/jedi/Projects/deep/data/mnist/')
batch_size = 64
Helper functions for network
anantzoid /
Created Nov 19, 2016
Summary for Conditional Image Generation with PixelCNN Decoder

Conditional Image Generation with PixelCNN Decoder



  • New image density model based on PixelCNN
  • Can generate variety of images from text embeddings or CNN layer weights
  • Serves as decoder in image autoencoder
  • Gated PixelCNN: Matches PixelRNN accuracy
anantzoid / The Technical Interview Cheat
Last active Sep 4, 2015 — forked from TSiege/The Technical Interview Cheat
This is my technical interview cheat sheet. Feel free to fork it or do whatever you want with it. PLEASE let me know if there are any errors or if anything crucial is missing. I will add more links soon.
View The Technical Interview Cheat

Studying for a Tech Interview Sucks, so Here's a Cheat Sheet to Help

This list is meant to be a both a quick guide and reference for further research into these topics. It's basically a summary of that comp sci course you never took or forgot about, so there's no way it can cover everything in depth. It also will be available as a gist on Github for everyone to edit and add to.

Data Structure Basics

###Array ####Definition:

  • Stores data elements based on an sequential, most commonly 0 based, index.
  • Based on tuples from set theory.