Neural Networks and TensorFlow - Deep Learning Series [Part 13]
In this tutorial we start looking into convolutional neural networks with TensorFlow.
First we're going to go through a little bit of theory and progressively we're going to get into coding. What we're gonna do is as first exercise is we'll train a convolutional neural network on the MNIST dataset.
We've worked with MNIST using softmax regression, and now we're going to go the CNN approach. Here's a breakdown of the following few tutorials:
- we're gonna build some helper functions to help us with the code
- we're gonna construct the computational graph and the architecture of the CNN
- we're gonna create a TensorFlow session and execute the graph - to train the CNN on the dataset
- we're gonna evaluate the performance.
Ok, so without further ado please see the tutorial for a more indepth breakdown of what's to come.
That's helpful programming, I appreciate your post.keep it up my dear friend...
Thank you @cristi for this educating yet really comprehensive post. I was almost getting confused at a point. To be honest though, most of the terms and things are still not fully understood but it is much better though, thanks to the fact that I watched the part 12 about two weeks ago.
Bit by bit I’ll surely get the main message.
Your voice is so cool by the way. 😎
Thank you for this educative post, though im not so versatile with this aspect of programming, but i keep resteeming because i never know who it might help. Thanks again