Leading corporations are betting their future on AI. In this 3-day hands-on workshop, you will learn best practices for neural network selection, tuning, training, and deployment into a production stack.
What You Will Achieve
Choosing an appropriate network for data analysis problems is a complex decision. In this introductory course, we will guide you from problem evaluation, model selection to ETL and data pipelines. You will acquire practical industry knowledge and leave with the ability to build production grade, end-to-end deep learning products with Deeplearning4j.
Who Should Attend?
This course is designed for data engineers, ETL (extract, transform, and load) developers, and data scientists who need to interact with big data infrastructure.
Attendees should be familiar with developing in Java (preferred) or Python. No prior knowledge of Deeplearning4j or neural networks is required.
This three-day hands-on class will cover the topics listed below.
History of Neural Networks
How to Choose an Appropriate Neural Network
Common Neural Network Architecture and Internals
Managing Data Pipelines and Data Injection with DataVec
Building Neural Networks with Deeplearning4j
Tuning Neural Network Hyperparameters
Training a Neural Networks
Deploying Neural Networks in a Production Environment
Skymind is the company behind Deeplearning4j, the only commercial-grade, open-source, distributed deep-learning library written in Java and Scala. Used by Fortune 500 corporations, DL4J is specifically designed to run in business environments on distributed GPUs and CPUs.