Deep Learning Part I
You'll learn the latest cutting-edge deep learning techniques in a practical, "top down" way, and train your own world-class models right from the first lesson. By the end of the course you'll have learned:
- How to create state of the art models in computer vision, natural language processing (NLP), recommendation systems, and tabular and time series data analysis
- How to use the brand new fastai v2 library along with PyTorch (the most popular software amongst top deep learning researchers)
- The foundations of deep learning: what is a neural network, how are they trained, and how do they make predictions
- How to turn your model into a real web application and how to debug your model if it goes wrong.
If you’re new to deep learning, don’t worry — we’ll take you through it all step by step. We do however assume that you’ve been coding for at least a year. You might be surprised by what you don’t need to become a top deep learning practitioner. You don’t need much data, you don’t need university-level math, and you don’t need a giant data center.
Deep Learning Part 1 is taught by Jeremy Howard, founding researcher at fast.ai and a Distinguished Research Scientist at USF. His most recent startup, Enlitic, was selected as one of the world's top 50 smartest companies by MIT Tech Review. Previously, Jeremy was President and Chief Scientist at Kaggle.
Deep Learning Changes Everything
Preview our Deep Learning Certificate with a lecture by instructor Jeremy Howard.
Continuing Education Units: 1.5