50+ keras interview questions and answers

In this article,  I am covering keras interview questions and answers only. I am not covering like regular questions about NN and deep learning topics here, If you are interested know  basics you can refer, datascience interview questions, deep learning interview questions.

What is Keras ?

Who is the Creator of Keras ?

François Chollet, He is currently working as an AI Researcher at Google

What is advantages of Keras ?

What is difference between keras and tensorflow ?

What is difference between keras and pytorch?

How to setup keras with tensorflow backend ?  

Types are layers in keras ?

• Core Layers
• Convolutional Layers
• Pooling Layers
• Locally-connected Layers
• Recurrent Layers
• Embedding Layers
• Merge Layers
• Advanced Activations Layers
• Normalization Layers
• Noise layers

What is input Layer ? When we will use this layer ?

What is Dense Layer ?  When we will use this layer ?

What is Convolutional Layer  ? When we will use this layer ?

What is Pooling Layer ? When we will use this layer ?

What is Locally Connected layers ? When we use this layers ?

What is Noise Layer ? When we will use this layer ?

What is Recurrent Layer ? When we will use this layer ?

What is Embedding Layer ? When we will use this layer ?

What is Merge Layer ? When we will use this layer ?

What is Normalization Layer ? When we will use this layer ?

What is Sequence Preprocessing in keras ?

What is Text Preprocessing in keras ?

What is Image Preprocessing in keras ?

What is activation function ?

Different Types of activation function in keras ?

Available activations

softmax

keras.activations.softmax(x, axis=-1)

elu

keras.activations.elu(x, alpha=1.0)

selu

keras.activations.selu(x)

softplus

keras.activations.softplus(x)

Softplus activation function.

softsign

keras.activations.softsign(x)

relu

keras.activations.relu(x, alpha=0.0, max_value=None, threshold=0.0)

tanh

keras.activations.tanh(x)

sigmoid

keras.activations.sigmoid(x)

hard_sigmoid

keras.activations.hard_sigmoid(x)

exponential

keras.activations.exponential(x)

linear

keras.activations.linear(x)

What are advanced activation functions in keras ?

LeakyReLU, PReLU

What are regularizers in keras ?

• keras.regularizers.l1(0.)
• keras.regularizers.l2(0.)
• keras.regularizers.l1_l2(l1=0.01, l2=0.01)

What is initializers in keras ?

What are Different Types of initializers in keras ?

Initializer

keras.initializers.Initializer()

Zeros

keras.initializers.Zeros()

Ones

keras.initializers.Ones()

Constant

keras.initializers.Constant(value=0)

RandomNormal

keras.initializers.RandomNormal(mean=0.0, stddev=0.05, seed=None)

RandomUniform

keras.initializers.RandomUniform(minval=-0.05, maxval=0.05, seed=None)

TruncatedNormal

keras.initializers.TruncatedNormal(mean=0.0, stddev=0.05, seed=None)

VarianceScaling

keras.initializers.VarianceScaling(scale=1.0, mode=’fan_in’, distribution=’normal’, seed=None)

Orthogonal

keras.initializers.Orthogonal(gain=1.0, seed=None)

Identity

keras.initializers.Identity(gain=1.0)

glorot_normal

keras.initializers.glorot_normal(seed=None)

glorot_uniform

keras.initializers.glorot_uniform(seed=None)

he_normal

keras.initializers.he_normal(seed=None)

lecun_normal

keras.initializers.lecun_normal(seed=None)

he_uniform

keras.initializers.he_uniform(seed=None)

How can you create custom initializer in keras ?

What is Callback in Keras ?

What are different types of callbacks in keras ?

• BaseLogger
• TerminateOnNaN
• ProgbarLogger
• History
• ModelCheckpoint
• EarlyStopping
• Arguments
• RemoteMonitor
• LearningRateScheduler
• TensorBoard
• ReduceLROnPlateau
• CSVLogger
• LambdaCallback

What are constraints in keras ?

What are available constraints in keras ?

• MaxNorm
• NonNeg
• UnitNorm
• MinMaxNorm

Different Types of metrics in keras ?

• binary_accuracy
• categorical_accuracy
• sparse_categorical_accuracy
• top_k_categorical_accuracy
• sparse_top_k_categorical_accuracy

Different types of loss functions in keras ?

• Mean_squared_error
• Mean_absolute_error
• Mean_absolute_percentage_error
• Mean_squared_logarithmic_error
• Squared_hinge
• Hinge
• Categorical_hinge
• Logcosh

What are predefined models in Keras for images Classification  ?

Models for image classification with weights trained on ImageNet:

• Xception
• VGG16
• VGG19
• ResNet50
• InceptionV3
• InceptionResNetV2
• MobileNet
• DenseNet
• NASNet
• MobileNetV2

How can you plot a graph in keras ?

What is functional API in Keras ?

What is model functions in Keras ?

Compile, fit, evaluate, Predict, fit_generator, evaluate_generator,

How can you specify batch in keras ?

How can you run a model in keras ?

What is difference between fit and fit_generator ?

How can you do normalization in keras ?

How can you save a model in keras ?

What are Model Optimization  ?

What are different types optimizers in keras ?

SGD – Stochastic gradient descent optimizer.
keras.optimizers.SGD(lr=0.01, momentum=0.0, decay=0.0, nesterov=False)
RMSprop – RMSProp optimizer.
keras.optimizers.RMSprop(lr=0.001, rho=0.9, epsilon=None, decay=0.0)
Adagrad – Adagrad optimizer
keras.optimizers.Adagrad(lr=0.01, epsilon=None, decay=0.0)
Adadelta – Adadelta optimizer.
keras.optimizers.Adadelta(lr=1.0, rho=0.95, epsilon=None, decay=0.0)
Adam – A Method for Stochastic Optimization
keras.optimizers.Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0.0, amsgrad=False)
Adamax
keras.optimizers.Adamax(lr=0.002, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0.0)
Nadam – Nesterov Adam optimizer.
keras.optimizers.Nadam(lr=0.002, beta_1=0.9, beta_2=0.999, epsilon=None, schedule_decay=0.004)

What learning rate ? How can you specify in keras ?

What is Error rate ? How can you decrease it ?

What is vanishing and exploding gradient problems?

How can you solve in gradient problems keras ?

How can you improve model accuracy in keras ?