What is Weight initialisation in TensorFlow?

Sharad Jaiswal
Sharad Jaiswal

Posted On: Nov 26, 2019

 

The initialization of weights is done in a random manner as this is critical for learning good mapping based on input and output in neural networks. This is necessary as the search space involving the weights is a large one and since there are multiple low minimums, the back-propagation might be trapped.

    Related Questions

    Please Login or Register to leave a response.

    Related Questions

    TensorFlow Interview Questions

    What is TensorFlow? Please Explain

    TensorFlow is a platform where one can learn machine learning / deep learning/multilayer neural networks from the Google library. Libraries that use data science are helpful to describe complex networ...

    TensorFlow Interview Questions

    Enlist few major features of the TensorFlow.

    Below are major features of TensorFlow:TensorFlow has the biggest ability is to build neural networks using which machines can develop logical thinking and learning analogous to humans. It is one...

    TensorFlow Interview Questions

    What are the tensors ? How many types of tensors are available?

    Tensors can be thought of as vectors and matrices of higher dimensions. They represent n-dimensional arrays of base data-type. Each element of a tensor is of the same data-type which is always known. ...