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# 
#  adult_LR_classifier.py    date. 10/17/2015
#    SGD (Stochastic Gradient Descent) version
#    consider 3 features of dataset
#   

import numpy as np
import numpy.random as rng
import matplotlib.pyplot as plt
import scipy as sp

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Logistic Regression Demo by TensorFlow

Logistic Regression is the basic concept of recent "Deep" neural network models. I rechecked TensorFlow L.R. coding to classify IRIS dataset.

• Binary Classification problem - iris_lr.py
• Multi-class Classification problem - iris_lr_softmax.py

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#
#  mnist_cnn_bn.py   date. 5/21/2016
#                    date. 6/2/2017 check TF 1.1 compatibility
#

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import os

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README.md

These codes are TensorFlow Autoencoder implementation examples. They are inspired by very educational Keras Blog article.

http://blog.keras.io/building-autoencoders-in-keras.html

Building Autoencodes in Keras

"Autoencoding" is a data compression algorithm where the compression and decompression

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#
#   tf_logistic_reg.py
#       date. 11/18/2015
#       date. 1/29/2017 - checked under tensorflow 0.12.1
#
#   The baseline is the code for 'Theano'.

from __future__ import print_function

import numpy as np

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Collaborative Filtering Tutorial Codes

The original codes comes from "Coursera Machine Learning" by prof. Andrew Ng, the program assignment of week 9.
I implemented this by Python,
1.Numpy + Scipy.Optimize
2.TensorFlow

• ex8_cofi.py: Numpy + Scipy.Optimize code
• check_costfun.py: support functions for ex8_cofi.py
• cofi_tf.py: TensorFlow code

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TensorFlow の名前空間を理解して共有変数を使いこなす

関連ファイル:

1. mnist_ae_varscope.py
2. mnist_2nets.py