.TensorFlow From CSV to API · Erik Erwitt
This tutorial illustrates one way to train a feed forward neural network based on a CSV file using TensorFlow. After training a model we’ll setup a small REST API to serve requests to predict Iris species based on their sepal length, sepal width, petal length and petal width. The REST API and work flow is meant to be as legible as possible to illustrate how to use these features. I’ve avoided adva
Machine Intelligence at Google Scale: Vision/Speech API, TensorFlow and Cloud Machine Learning
The biggest challenge of Deep Learning technology is the scalability. As long as using single GPU server, you have to wait for hours or days to get the result of your work. This doesn't scale for production service, so you need a Distributed Training on the cloud eventually. Google has been building infrastructure for training the large scale neural network on the cloud for years, and now started
[TF]TensorflowのAPIについて - Qiita
Constant Value Tensors zeros numpyのzerosみたいなもの TensorのデータタイプとShapeを指定する import tensorflow as tf x = tf.zeros([1], dtype=tf.float32) with tf.Session() as sess: print(x.eval()) [ 0.] import tensorflow as tf x = tf.zeros([10], dtype=tf.float32) with tf.Session() as sess: print(x.eval()) [ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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GitHub - tflearn/tflearn: Deep learning library featuring a higher-level API for TensorFlow.
GitHub - tensorflow/skflow: Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
