Top 20 Interview Questions on Keras You Must Practice

If you are into deep learning and artificial intelligence, you must be familiar with Keras. One of the most popular Deep Learning frameworks – Keras has become the go-to choice of Data Scientists due to its smooth, high-level, and user-friendly interface. Keras has made it easier for Data Science beginners to dive into deep learning and easily develop applications without getting trapped into complex computations.

With the field of deep learning growing every day, its applications and demand have also increased exponentially. Companies and Data Scientists are actively using deep learning frameworks such as Keras and TensorFlow to develop desired models and applications. 

Consequently, when hiring for a Data Scientist, companies look for candidates with extensive knowledge of Deep Learning and AI along with hands-on experience in Keras and TensorFlow. If you’re interviewing for a Data Scientist position that involves tasks in deep learning and AI, you are likely to be asked questions on these frameworks.

To help you prepare, in this article we’ll discuss the top 20 questions on Keras you can be asked in Data Scientist interviews. Earlier, we talked about interview questions on Tensor. Let’s get started. 

Top 20 interview questions on Keras 

  1. What is Keras?
  2. Define flatten layer in Keras
  3. What do you understand by Keras dropout?
  4. Name the different types of layers in Keras. 
  5. State three differences between Keras and TensorFlow
  6. What is the use of recurrent layers in Keras?
  7. Explain the term sequence preprocessing in Keras
  8. Define an activation function. 
  9. Differentiate between the input and dense layer. 
  10. What is an embedding layer? What is its use?
  11. Name the different types of activation functions in Keras. 
  12. Explain the regularizers in Keras.
  13. Name the various types of callbacks in Keras. 
  14. What are the different types of metrics in Keras?
  15. Define loss function in Keras. 
  16. Differentiate between the learning rate and error rate. 
  17. How will you decrease the error rate in Keras?
  18. What is the use of Adagrad optimizer in Keras?
  19. How will you specify a batch in Keras?
  20. Explain how will you plot a graph in Keras?

If you have a Data Scientist interview coming up, check out our series on popular Data Science interview questions. 

  1. Top interview questions on NLP
  2. Common Python interview questions
  3. 20 Machine Learning interview questions and answers

We hope you found these questions on Keras useful. If you have any Data Science related questions drop a comment below and we will get back to you.

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