David Paper - TensorFlow 2.x in the Colaboratory Cloud: An Introduction to Deep Learning on Google’s Cloud Service

Download this books example data by clicking the Download source code button found on the books catalog page at www.apress.com/us/book/9781484266489 . It can also be downloaded directly from www.github.com/Apress/tensorflow-2.x-in-the-colab-cloud .

We introduce the basic concepts of deep learning. We use TensorFlow 2.x, the Google cloud service, and Google Drive Interactive to make the concepts come alive with Python coding examples.

Notebooks for chapters are located at the following URL: https://github.com/paperd/tensorflow .

So what is deep learning ? Deep learning is a machine learning technique that provides insights from data through automated learning algorithms with the purpose of informing decision making. Deep learning algorithms use successive layers to progressively extract higher-level features from raw input. Whew, thats a mouthful. Lets break it down a bit. Deep learning emphasizes learning successive layers of increasingly meaningful representations from the data. Each layer of a deep learning model learns from the data. So each layer passes down what it learns to the next layer. In image processing, lower layers may identify edges, while higher layers may identify concepts relevant to a human such as digits, letters, or faces. Dont worry if this is confusing because we have yet to define the basics, which we are about to do now.