tomokishii

#
#  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

tomokishii

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

tomokishii

#
#   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

tomokishii

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

tomokishii

PyTorch Logistic Regression ~ MLP model

1. logistic_regression.py - Using torch.nn module, analysing sklearn DIGITS dataset
2. logistic_regression_low.py - NOT using torch.nn module, analysing sklearn DIGITS dataset
3. mnist_mlp.py

tomokishii

Chainer vs. PyTorch Linear Regression

1. linear_reg_chainer.py (Chainer version)
2. linear_reg_pytorch.py (PyTorch version)

• Python 3.5.2 (or 3.5.3)
• Chainer 2.0.0
• PyTorch 0.1.12

tomokishii

Modern Gradient Boosting models - how to use GridSearchCV

My current environment is...

• Python 3.5.2
• Scikit-learn 0.18.1
• XGBoost (python-package) 0.6
• LightGBM (python-package) v2.0

tomokishii

tomokishii

# 
#  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

tomokishii

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