# Write predict code using concat_examples

This tutorial corresponds to 03_custom_dataset_mlp folder in the source code.   We have trained the model with own dataset, MyDataset, in previous post, let’s write predict code. Source code: predict_custom_dataset1.py predict_custom_dataset2.py   Prepare test data It is not difficult for the model to fit to the train data, so we will check how the model is […]

# Training code for MyDataset

This tutorial corresponds to 03_custom_dataset_mlp folder in the source code. We have prepared your own dataset, MyDataset, in previous post. Training procedure for this dataset is now almost same with MNIST traning. Differences from MNIST dataset are, This task is regression task (estimate final “value”), instead of classification task (estimate the probability of category) Training […]

# Create dataset class from your own data with DatasetMixin

This tutorial corresponds to 03_custom_dataset_mlp folder in the source code. In previous chapter we have learned how to train deep neural network using MNIST handwritten digits dataset. However, MNIST dataset has prepared by chainer utility library and you might now wonder how to prepare dataset when you want to use your own data for […]

# Predict code for simple sequence dataset

Predict code is easy, implemented in predict_simple_sequence.py. First, construct the model and load the trained model parameters,

Then we only specify the first index (corresponds to word id), primeindex, and generate next index. We can generate next index repeatedly based on the generated index.

The result is the following, successfully generate […]

# Chainer v2 released: difference from v1

Chainer version 2 has been released on 2017 June 1,  #Chainer v2.0.0 has been released! Memory reduction (33% in ResNet), API clean up, and CuPy as a separate package. https://t.co/xRrmZAlJWT — Chainer (@ChainerOfficial) June 1, 2017 This post is a summary of what you need to change in your code for your chainer development. Detail […]

# Training RNN with simple sequence dataset

We have learned in previous post that RNN is expected to have an ability to remember the sequence information. Let’s do a easy experiment to check it before trying actual NLP application. Simple sequence dataset I just prepared a simple script to generate simple integer sequence as follows, Source code: simple_sequence_dataset.py

Its output is, […]

# Recurrent Neural Network (RNN) introduction

[Update 2017.06.11] Add chainer v2 code   How can we deal with the sequential data in deep neural network? This formulation is especially important in natural language processing (NLP) field. For example, text is made of sequence of word. If we want to predict the next word from given sentence, the probability of the next […]

# CIFAR-10, CIFAR-100 inference code

The code structure of inference/predict stage is quite similar to MNIST inference code, please read this for precise explanation. Here, I will simply put the code and its results. CIFAR-10 inference code Code is uploaded on github as predict_cifar10.py.

This outputs the result as, You can see that even small CNN, it successfully classifies most […]

# CIFAR-10, CIFAR-100 training with Convolutional Neural Network

[Update 2017.06.11] Add chainer v2 code Writing your CNN model This is example of small Convolutional Neural Network definition, CNNSmall

I also made a slightly bigger CNN, called CNNMedium,

It is nice to know the computational cost for Convolution layer, which is approximated as,  H_I \times W_I \times CH_I \times CH_O \times k ^ […]