Neural Networks Flashcards
(7 cards)
What is a neural network?
A neural network is a machine learning program, or model, that makes decisions in a manner similar to the human brain, by using processes that mimic the way biological neurons work together to identify phenomena, weigh options and arrive at conclusions.
What are nodes?
artificial neurons—an input layer, one or more hidden layers, and an output layer. Each node connects to others, and has its own associated weight and threshold. If the output of any individual node is above the specified threshold value, that node is activated, sending data to the next layer of the network. Otherwise, no data is passed along to the next layer of the network.
What are neural networks comprised of?
Input layer, hidden layers, output layers
What are Convolutional Neural Networks CNNs
These networks harness principles from linear algebra, particularly matrix multiplication, to identify patterns within an image. Common in image recognition, pattern recognition, and computer vision
What is Recurrent neural networks RNNs
are identified by their feedback loops. These learning algorithms are primarily leveraged when using time-series data to make predictions about future outcomes, such as stock market predictions or sales forecasting.
What are feedforward Neural networks?
They are comprised of an input layer, a hidden layer or layers, and an output layer. Data is fed through them and they are the foundation for computer vision and NLP
What is the difference between an neural network and deep learning?
A neural network that consists of more than three layers—which would be inclusive of the inputs and the output—can be considered a deep learning algorithm. A neural network that only has two or three layers is just a basic neural network.
