Tensorflow on Google's Cloud Platform for Data Engineers

Welcome to Tensorflow on the Google Cloud Platform for Data Engineers This is the fourth course in a series of courses designed to help you attain the coveted Google Certified Data Engineer. Additionally, the series of courses is going to show you the role of the data engineer on the Google Cloud Platform. NOTE: This is not a course on how to develop machine learning models with TensorFlow.

This is a very targeted course on TensorFlow for data engineers. My goal is to give data engineers what they need to know for the exam and provide learners with the foundations of TensorFlow on Google's Cloud Platform. At this juncture the Google Certified Data Engineer is the only real world certification for data and machine learning engineers.

TensorFlow is an open source software library created by Goggle for doing graph-based computations quickly. It does this by utilizing the GPU(Graphics Processing Unit) and also making it easy to distribute the work across multiple GPUs and computers. Tensors, in general, are simply arrays of numbers, or functions, that transform according to certain rules under a change of conditions.

Nodes in the graphs represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. In the course you'll discover how to apply TensorFlow to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessions and the computation graph. You'll work with basic math operations and image transformations to see how common computations are performed.