TensorFlow Interview Questions & Answers

About TensorFlow Interview Questions & Answers

A warm welcome to the

TensorFlow Interview Questions & Answers

course by

Uplatz

.

Uplatz

provides this course on TensorFlow Interview Questions. You will learn the most frequently asked questions in TensorFlow engineer job interviews. As per the leading job sites, the average salary for TensorFlow jobs is

$148,000

. Thus Deep Learning engineers with sound knowledge of TensorFlow command premium salaries, hence it's a good area to be already in or to aspire for.

What is TensorFlow

TensorFlow is a powerful data flow oriented machine learning Generally, it can think of as a programming system in which you represent computations as graphs. Nodes in the graph represent math operations, and the edges represent multidimensional data arrays (tensors) communicated between them. Thus TensorFlow is an open source deep learning library that is based on the concept of data flow graphs for building models. It allows you to create large-scale neural networks with many layers.

Tensors and TensorFlow

Tensors are nothing but a de facto for representing the data in deep learning. 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. In TensorFlow, the term tensor refers to the representation of data as multi-dimensional array whereas the term flow refers to the series of operations that one performs on tensors. The overall process of writing a TensorFlow program involves two steps: 1. Building a Computational Graph 2. Running a Computational Graph TensorFlow bundles together Machine Learning and Deep Learning models and algorithms. It uses Python as a convenient front-end and runs it efficiently in optimized C++. TensorFlow allows developers to create a graph of computations to perform. Each node in the graph represents a mathematical operation and each connection represents data. Hence, instead of dealing with low-details like figuring out proper ways to hitch the output of one function to the input of another, the developer can focus on the overall logic of the application.