How to use this course
Practical Deep Learning For Coders is designed to take anyone with at least one year's coding experience to the point they can apply deep learning best practices to create state of the art models in computer vision, natural language, and recommendation systems. The course is fairly general and students should be able to apply the techniques to other areas as well. The course consists of the following pieces:
- Seven full video lessons of a little over 2 hours each, plus two shorter introductory videos
- A set of detailed notebooks showing how to complete the steps demonstrated in each video.
- The forums, which should be your first step for asking questions not answered by the wiki or course notes. Be sure to search the forum before asking your question, since many questions have been answered already. If you do ask a question, please do it in the thread for the appropriate lesson or topic, if there is one
How to get started
Since this is a code-focussed course, you need access to a computer with an Nvidia GPU, along with a python-based deep learning stack set up on it. In the first lesson we show how to easily set up a cloud GPU computer.
We suggest you have the notebook in front of you as you watch the video, or else watch the video and then read through the notebook. The notebooks have quite a bit of extra information, and most importantly, they let you experiment. Experimenting is the secret to developing a strong intuition for deep learning architectures and training!
Now you're ready to watch Lesson 1! And if you get stuck, don't hesitate to ask for help.
