Top 10 Interview QA on Theano & KNIME


1. What is Theano ?
Ans: Theano is a Python library that lets you define mathematical expressions used in Machine Learning, optimize these expressions and evaluate those very efficiently by decisively using GPUs in critical areas.

2. Where was Theano written ?
Ans: Theano was written at the LISA lab with the intention of providing rapid development of efficient machine learning algorithms.

3. What is the use of dscalar method ?
Ans: The dscalar method declares a decimal scalar variable.

4. In Theano how to optimize the execution of an expression ?
Ans: Theano uses advanced optimization techniques to optimize the execution of an expression. To visualize the computation graph, Theano provides a printing package in its library.

5. What is the use of shared variables ?
Ans:  Typically, Theano moves such shared variables to the GPU, provided one is available. This speeds up the computation.

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6. What is the role of Theano function ?
Ans: Theano function acts like a hook for interacting with the symbolic graph. A symbolic graph is compiled into a highly efficient execution code. It achieves this by restructuring mathematical equations to make them faster. It compiles some parts of the expression into C language code.

7. What is the role of Knime ?
Ans: KNIME provides a graphical interface for development.

8. What KNIME provides ?
Ans: KNIME provides several predefined components called nodes for various tasks such as reading data, applying various ML algorithms, and visualizing data in various formats.

9. Where can we create machine learning model ?
Ans: The most important view for us is the Workspace view. This is where you would create your machine learning model.

10. What is the role of workspace view ?

Ans: The workspace view may not be able to show you the entire workflow at a time. That is the reason, the outline view is provided.



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