Learn to build and train your own neural networks for artificial intelligence. Videos review foundational concepts and cover the training and validation of networks.

Course Overview
Neural networks are becoming better and increasingly more popular for machine learning and artificial intelligence applications due to more data and better technology being available. Learn how neural networks can be viewed as differentiable programs in the context of calculus. The course covers fundamental concepts related to building, training and validating neural net models. Examples will include both linear and nonlinear regression models as well as classification tasks, specifically image classification. See how the symbolic nature of Wolfram Language and the Neural Net Framework itself make it easy to take apart layers in the network and create visualizations to help you understand how it works.

Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One), Wolfram Neural Net Framework
You'll Learn To

Identify the advancements that have made neural networks better and more popular in recent years
View neural networks as differentiable programs in the context of mathematical operations from calculus
Build simple net models for regression and classification

Train different models with the help of available data
Fine-tune and validate the performance of models with the help of additional data
Explore the Neural Net Repository

Video Duration

Video 111 minutes
Video 28 minutes
Video 311 minutes
Video 47 minutes
Video 54 minutes
Video 617 minutes
Video 76 minutes
Video 84 minutes
Video 912 minutes
Video 104 minutes
Video 1119 minutes

Syllabus

Identify the advancements that have made neural networks better and more popular in recent years
View neural networks as differentiable programs in the context of mathematical operations from calculus
Build simple net models for regression and classification
Train different models with the help of available data
Fine-tune and validate the performance of models with the help of additional data
Explore the Neural Net Repository