Pontifications

“To be exact, after reading this book you will know:
- How to train models that achieve state of the art results in:
  - Computer vision: Image classification (e.g. classify pet photos by breed), and image localization and detection (e.g. find where the animals in an image are)
  - Natural Language Processing (NLP): Document classification (e.g. movie review sentiment analysis), and language modelling
  - Tabular data (e.g. sales prediction) with categorical data, continuous data, and mixed data, including time series
  - Collaborative filtering (e.g. movie recommendation)
”<— from: Howard and Gugger: Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD (book website includes GPU options and other Jupyter administrivia) <— sounds too good to be true :-) but the jupyter notebooks sound great