- Deep Learning
- Neural Network Framework
- Model Repository
- Network Layers
- Network Surgery
- Image Identification
- Natural Language Understanding
- Speech Analysis
In this one-week boot camp, you'll learn what neural networks are, how to work with pre-trained networks and how to build and train your own models. You'll also have the chance to explore deep learning applications in text, image and audio analysis. All campers will receive a certificate of boot camp completion. Campers who demonstrate proficiency through boot camp exercises will become Wolfram Certified Level I in neural networks.
The high-performance neural net framework integrated in the Wolfram Language makes it easy to build networks from a wide variety of encoders, decoders and other symbolic layers. These networks can be immediately trained and deployed for use in different applications. All this can often be done with only a few lines of code, making deep learning accessible and approachable for new or existing Wolfram Language users and anyone wanting to learn about neural networks.Neural Networks in the Wolfram Language »
Tech mentors will be available throughout the camp for guidance and assistance.
Topic introductions and concept lectures
Working lunches with instructors, tech mentors and campers
Hands-on exercises and application of concepts and topics
Anyone who wants to learn about deep learning—at any stage of their career or education.
You'll need a laptop computer and the willingness to explore.
None! The extreme automation of the Wolfram Language means it's easy for anyone to do high-level programming. The model repository includes a collection of pre-trained networks, so you can get started right away. If you have experience with the Wolfram Language, you'll be at an advantage. The first morning of the boot camp (optional for experienced users) will be devoted to introducing the basics of Wolfram Notebooks and the Wolfram neural net framework. If needed, there will be tutors available to provide hands-on help for getting started.
Neural networks uses concepts from calculus, linear algebra, statistics and probability theory. Some helpful resources are available at Wolfram U.
In addition to hands-on knowledge of neural networks, you'll know how to use trained and untrained models from the Wolfram Neural Net Repository and how to build and train your own models. All campers will receive a certificate of boot camp completion. Campers who demonstrate proficiency through boot camp exercises will become Wolfram Certified Level I in neural networks.
To optimize the peer learning experience, we suggest that data brought to the boot camp is something that can be shared with other attendees. However, special arrangements can be made, and our instructors will be operating under our standard corporate NDA.
While the Wolfram Summer School is a selective program for experienced Wolfram Language users who want to carry out original projects using Wolfram methodologies, the Neural Networks Boot Camp is intended for a broader audience and concentrates specifically on neural networks.
The one-week program costs $1,200 for industry or commercial attendees, $600 for teachers or professors and $300 for students. Your boot camp registration includes lecture and exercise notebooks and 30-day access to Wolfram|One. It also includes access to high-speed internet and daily group lunches.
The boot camp will be held at Wolfram corporate headquarters, 100 Trade Center Drive, Champaign, Illinois, USA.
Since Champaign is a university town, there are many options for housing available.
We are closely monitoring federal agencies' recommendations to plan for a safe event. We are proceeding with the boot camp with the health and safety of our attendees and staff as our top priority.
You can cancel your registration before March 2 for a full refund. Cancellations due to the rapidly changing coronavirus disease 2019 (COVID-19) situation will be fully refunded up to the start of the boot camp. Should the COVID-19 situation require cancellation of the boot camp, Wolfram will work to provide alternate methods of instruction to participants, including online lecture sessions.