Tensorflow on Batı Şengül
http://www.batisengul.co.uk/tags/tensorflow/
Recent content in Tensorflow on Batı ŞengülHugo -- gohugo.iobatisengul@gmail.combatisengul@gmail.comWed, 20 Nov 2019 00:00:00 +0000Wasserstein variational autoencoders
http://www.batisengul.co.uk/post/2019-11-20-wasserstein-vae/
Wed, 20 Nov 2019 00:00:00 +0000batisengul@gmail.comhttp://www.batisengul.co.uk/post/2019-11-20-wasserstein-vae/Variational auto-encoders (VAEs) are a latent space model. The idea is you have some latent space variable $z \in \mathbb{R}^{k}$ which describes your original variables $x\in\mathbb{R}^d$ in higher dimensional space by a latent model $p(x|z)$. Let’s assume that this distribution is given by a neural network with some parameters $\theta$ so that we assume $$ x | z, \theta \sim N(g_\theta(z), 1). $$ Of course in reality, we don’t know $(z, \theta)$, we would like to infer these from the data.Introduction To Tensorflow Estimator
http://www.batisengul.co.uk/post/2019-11-19-introduction-to-tensorflow-estimator/
Tue, 19 Nov 2019 00:00:00 +0000batisengul@gmail.comhttp://www.batisengul.co.uk/post/2019-11-19-introduction-to-tensorflow-estimator/In this post I am going to introduce tf.estimator library. So first of all, what is this library trying to do? When writing tensorflow code, there is a lot of repeated operations that we need to do:
read the data in batches process the data, e.g. convert images to floats run a for loop and take a few gradient descent steps save model weights to disk output metrics to tensorboard The keras library makes this quite a bit easier, but there are times when you might need to use plain old tensorflow (it gets quite hacky to implement some multiple output models and GANs in keras).