Machine Learning Algorithms - Part II Exercises (Part 1)

Question 1 of 7

1. Question

Artificial Neural Networks try to simulate the way neurons in the human brain work

True
False

Question 2 of 7

2. Question

The first artificial neural network / neuron was called:

The Neurotron
Deep learning
The Perceptron
Inception

Question 3 of 7

3. Question

Deep Learning increases the power of neural networks by:

Adding many hidden layers in different combinations
Adding many input layers in different combinations
Adding many output layers in different combinations
Adding many invisible layers in different combinations

Question 4 of 7

4. Question

Deep Learning is the use of many, many hidden layers to handle greater complexity in classification and other neural network machine learning capabilities.

True
False

Question 5 of 7

5. Question

When selecting algorithms, deep learning will always be the best algorithm.

True
False

Question 6 of 7

6. Question

What is a neuron node?

A hidden layer in a neural network
An ensemble of different models
aggregation of all the losses / errors in a neural network during one pass of training
A point in a neural network in which accepts one or more weighted input connections with adjustments, a function that combines those inputs, and an activation function that provides an output

Question 7 of 7

7. Question

Match the neural network term to the definition:

Sort elements

Activation Function
Weight
Neural network Bias
Hidden Layer

Function that determines at what threshold a neuron will “activate” and provide an output.

strength of a particular connection between a neuron and the neuron in the next or previous layer

An adjustment to the sum of all the input weights that is provided ot the activation function

One of the layers in a neural network that sits between the input layer and output layer