Introduction to Deep Learning

Meet your instructor, get an overview of the course, and find a few interesting resources in this introductory lesson.

This introductory lesson on Deep Learning covers how experts think about deep learning and how to know when deep learning is the right tool for the job, including some examples.

Beginning with PyTorch and moving into both Error Functions, Gradient Descent, and Backpropagation, this lesson provides an overview of foundational neural network concepts.

This introduction to neural networks explains how algorithms inspired by the human brain operate and puts to use those concepts when designing a neural network to solve particular problems.

Learn how to train neural networks and avoid overfitting or underfitting by employing techniques like Early Stopping, Regularization, Dropout, Local Minima, and Random Restart!