Deep Learning - Crash Course 2023 - Moving from Shallow Learning to Deep Learning

The video tutorial introduces the concepts of shallow and deep learning, explaining the structure of deep learning neural networks. It demonstrates building a neural network using the Keras library in Python, focusing on sigmoid neurons and layer connections. The tutorial covers training the model to achieve high accuracy and provides an assignment for further exploration.

What does the term 'deep' in deep learning refer to?

• The depth of understanding required

• The amount of data processed

• The number of layers in the model

• The complexity of the data

Which type of neuron is considered the building block of deep neural networks?

• Perceptron

• Sigmoid Neuron

• NP Neuron

• Sigma Neuron

In a neural network, how does the second layer receive its input?

• From an external data source

• From the output of the first layer

• Directly from the input layer

• It generates its own input

What is the activation function used in the first layer of the Keras model described?

• ReLU

• Tanh

• Sigmoid

• Softmax

What learning algorithm is used in the Keras model compilation?

• Stochastic Gradient Descent

• Adagrad

• RMSprop

• Adam

What was the achieved accuracy after 1000 epochs in the Keras model?

• 50%

• 75%

• 85%

• 98%

What are students encouraged to do in the assignment?

• Create a new dataset

• Read more about deep learning

• Experiment with different values of units and layers

• Write a report on neural networks