After my teammates and I had completed our implementation of CycleGANs for our Computer Vision class project, we needed GPUs to run the python script containing the tensorflow code. Since we had multiple datasets, we could not run the code using a single dataset on the Blue Waters quota allotted to us and wait for it to get done. We needed more GPUs!!! So, while my teammates were involved in running it on Blue Waters, I decided to give Google Cloud Platform a try. After going through multiple blogs and tutorials to set up GPUs and tensorflow on Google Cloud, I realized that none of them would give me all the details in one place and therefore, I was compelled to write this blog to provide a step by step procedure on how to set up GPUs and tensorflow on Google Cloud Platform from start to finish. So lets get right to it.
This is how simple neurons get smarter and perform so well for certain problems such as image recognition and playing Go. Inception: an image recognition model published by Google (From: Going deeper with convolutions, Christian Szegedy et al.) Some published examples of visualization by deep networks show how they're trained to build the hierarchy of recognized patterns, from simple edges and blobs to object parts and classes. In this article, we looked at some TensorFlow Playground demos and how they explain the mechanism and power of neural networks. As you've seen, the basics of the technology are pretty simple.
In this module, we will implement a neural network application using TensorFlow on E-commerce data set. We will predict the yearly amount spent by each customer based on their browsing behavior. The data set is already loaded in the exercises below so you just have to understand the code and run it to check the output. TensorFlow is a software framework for building and deploying machine learning models. It provides the basic building blocks to design, train, and deploy machine learning models.
In the past few days, I've taught a machine learning algorithm how to write in the style of Harry Potter, Hamilton (the musical), and HBO's Silicon Valley. The mostly non-sensical, occasionally human-like, topically-flavored writing seems to be amusing not only to me, but to many others. Thus, I've made this quick tutorial to teach you how to create your own instances of "Deep Writing". This is not going to be an in-depth description of the underlying technology -- but instead, a step-by-step guide that anybody can follow (even if you have no coding or machine learning experience). Here is a very crude approximation of what is involved in the Deep Writing process.