AI & Analytics
Neural networks with an application in R/H2O
Aspiring Data Scientists with a wish to deepdive on the most important technologies.
Interactive classroom training combining theory with practical exercises
Knowledge of programming basics (not necessarily in R)
Bring a laptop with Rstudio and H2O library installed
Prefered group size:
8 participants per trainer (scalable)
During this training, participants will get an introduction to feed-forward Neural Networks, and gain an understanding of how they work, what their strengths and weaknesses are, and how they can train and utilize neural networks. Starting from exercises on paper, the session builds up to training small networks on practice data sets. As final touch deep learning is applied on a face recognition task using raw images.
Upon completion of this training, participants will be able to decide when a neural network is applicable, how to decide on its number of layers and layer size, and how to train a neural network model.