This case study explores the basics of deep learning. In the first portion of the case study, training of a neural network is performed with a numpy implementation, then we explore supervised and unsupervised techniques on a spoken digit recognition task.
Without GPU (CPU only):
If using a GPU:
The docker images for this case study are located on dockerhub. Running the commands below will automatically download and start a jupyter notebook.
Run the Docker image for CPU only computation:
docker run -p 8888:8888 --rm springernlp/chapter_4:latest
Run the Docker image with GPU access:
docker run --runtime=nvidia -p 8888:8888 --rm springernlp/chapter_4:latest
docker build -t chapter_4:latest .
More information can be found at: Deep Learning for NLP and Speech Recognition by Springer