Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

LinkedIn Learning

Deep Learning: Getting Started

via LinkedIn Learning


Learn the basics of deep learning and get up and running with this technology.


  • Getting started with deep learning
  • Prerequisites for the course
  • Setting up the environment
1. Introduction to Deep Learning
  • What is deep learning?
  • Linear regression
  • An analogy for deep learning
  • The perceptron
  • Artificial neural networks
  • Training an ANN
2. Neural Network Architecture
  • The input layer
  • Hidden layers
  • Weights and biases
  • Activation functions
  • The output layer
3. Training a Neural Network
  • Setup and initialization
  • Forward propagation
  • Measuring accuracy and error
  • Back propagation
  • Gradient descent
  • Batches and epochs
  • Validation and testing
  • An ANN model
4. Deep Learning Example 1
  • The Iris classification problem
  • Input preprocessing
  • Creating a deep learning model
  • Training and evaluation
  • Saving and loading models
  • Predictions with deep learning models
5. Deep Learning Example 2
  • Spam classification problem
  • Creating text representations
  • Building a spam model
  • Predictions for text
6. Deep Learning Exercise
  • Exercise problem statement
  • Preprocessing RCA data
  • Building the RCA model
  • Predicting root causes with deep learning
  • Extending your deep learning education

Taught by

Kumaran Ponnambalam


4.6 rating at LinkedIn Learning based on 154 ratings

Start your review of Deep Learning: Getting Started

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.