TensorFlow Tutorial

Ashish Bakshi has a TensorFlow tutorial:

As shown in the image above, tensors are just multidimensional arrays, that allows you to represent data having higher dimensions. In general, Deep Learning you deal with high dimensional data sets where dimensions refer to different features present in the data set. In fact, the name “TensorFlow” has been derived from the operations which neural networks perform on tensors. It’s literally a flow of tensors. Since, you have understood what are tensors, let us move ahead in this TensorFlow tutorial and understand – what is TensorFlow?

The sample here is Python, though there is an R library as well.

Related Posts

P-Hacking and Multiple Comparison Bias

Patrick David has a great article on hypothesis testing, p-hacking, and multiple comparison bias: The most important part of hypothesis testing is being clear what question we are trying to answer. In our case we are asking:“Could the most extreme value happen by chance?”The most extreme value we define as the greatest absolute AMVR deviation from […]

Read More

Feature And Text Classification Using Naive Bayes In R

I wrap up my series on the Naive Bayes class of algorithms, finally writing some code along the way: Now we’re going to look at movie reviews and predict whether a movie review is a positive or a negative review based on its words. If you want to play along at home, grab the data set, […]

Read More

Categories

November 2017
MTWTFSS
« Oct Dec »
 12345
6789101112
13141516171819
20212223242526
27282930