What is the difference between one to one, one to many, many to one, many to many in Neural Network?
Ans: In a One-To-Many relationship, one object is the "parent" and other is the "child". The parent controls the presence
Explain Recurrent Neural Network?
Ans: Recurrent Neural Network are a type of Neural Network where the output from previous step are fed as input to the current step.
When do we apply early stopping and how it is helpful?
Ans: Early Stopping is a type of regularization technique. During training, the model is evaluated on a holdout validation dataset
Explain Data Augmentation? What are its uses?
Ans: Data augmentation adds value to base data by adding information derived from internal and external sources within an original
What are the Regularization techniques used in Neural Network?
Ans: Regularization is a technique which makes slight modifications to the learning algorithm such that the model generalizes better. This
How can you understand under fitting and over fitting in Neural Network?
Ans: A model is said to have underfitting when it cannot capture the underlying trend of the data. Underfitting destroys
What are different hyperparameters use in Convolutional Neural Networks during training model?
Ans: Hyperparameter tuningTuning hyperparameters for deep neural network is difficult because it is slow to train a deep neural network
Why we use only Convolutional Neural Network for the Image recognition?
Ans. Convolutional Neural Network is developed from the inspiration of the visual cortex in Human Brain. CNN are the complex
What is the difference between Convolutional Neural Network and Capsule Neural Network?
Ans: Convolutional Neural Network is used for the Image recognition by using different layers. Convolutional layer comprises set of independent
What do you mean by Capsule Neural Network?
Ans: Capsule is a nested set of neural layers. In a regular neural network, you keep on adding more layers