Build & Train RNNs: Neural Network Components
Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level
Overview/Description
Explore artificial neural network and the components of neural networks and examine the concept of learning and training samples used in Supervised, Unsupervised and Reinforcement learning.

Expected Duration (hours)
0.6

Lesson Objectives Build & Train RNNs: Neural Network Components

describe artificial neural network and its components
identify the topology of the networks that implements feedforward, recurrent and linked networks
list activation mechanisms used in the implementation of neural networks
specify the prominent learning samples that can be applied in neural networks
compare Supervised, Unsupervised, and Reinforcement learning samples
describe training samples and the approaches for building them
identify training sets and recognize patterns
recognize the need for gradient optimization in neural networks
list neural network components, activation functions, learning samples, and gradient descent optimization algorithms

Course Number: it_mlbtrndj_01_enus

Expertise Level
Intermediate