TensorFlow Interview Questions and Answers 2019

TensorFlow Interview Questions and Answers 2019

TensorFlow is an open source framework, by Google for creating deep learning models. Deep Learning is one of several categories of machine learning (ML) models that use multi-layer neural networks. TensorFlow is cross-platform. It runs on nearly everything: GPUs and CPUs—including mobile and embedded platforms—and even tensor processing units (TPUs), which are specialized hardware to do tensor math on The TensorFlow library allows users to perform functions by creating a computational graph. TensorFlow provides a variety of different toolkits that allow you to construct models at your preferred level of abstraction. You can use lower-level APIs to build models by defining a series of mathematical operations

What is TensorFlow?

What is TFT?

Explain Eager Execution?

What are the Features of Eager Execution?

What if a file is corrupted or missing in a dataset?

How does TensorFlow fit into AI and Machine learning?

What is the application of Naïve Bayes Naïve in Machine Learning?

What difference do you find in type1 and type 2 errors?

How useful and reliable Bayes’ theorem is according to you in the Machine Learning context?

How K-means clustering is different from KNN?

What are TensorFlow loaders?

What is ROC curve and its working?

Can TensorFlow be deployed in container software?

What is Sequence-to-Sequence model?

What is Keras?

What is Max pooling?

What are the APIs outside TensorFlow project?

What are the TensorFlow operations?

What are the Sequence Utilities methods?

What is Reduction?

What are the cons of TensorFlow?

Can you explain Embedding in TensorFlow?

What is TensorFlow Mobile?

Can you explain Data Formats in TensorFlow?

Explain TensorFlow Optimizing for CPU?

What is MNIST Dataset in TensorFlow?

What is the tfdbg TensorFlow Debugging?

What are the Common TensorFlow Operations?

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