Neural Networks and Deep Learning - Part II (Practice)
Dr. Hua Zhou
3/15/2018
Software
High-level software focuses on user-friendly interface to specify and train models.
Keras, PyTorch (only Linux and MacOS), scikit-learn, …Lower-level software focuses on developer tools for impelementing deep learning models.
TensorFlow, Theano, CNTK, Caffe, Torch, …Most tools are developed in Python plus a low-level language.
TensorFlow
Developed by Google Brain team for internal Google use. Formerly DistBelief.
Open sourced in Nov 2015.
OS: Linux, MacOS, and Windows (since Nov 2016).
GPU support: NVIDIA CUDA.
TPU (tensor processing unit), built specifically for machine learning and tailored for TensorFlow.
Mobile device deployment: TensorFlow Lite (May 2017) for Android and iOS.
Used in a variety of Google apps: speech recognition (Google assistant), Gmail (Smart Reply), search, translate, self-driving car …
when you have a hammer, everything looks like a nail.
- Machine Learning Crash Course (MLCC). A 15 hour workshop available to public since March 1, 2018.
R/RStudio
R users can access Keras and TensorFlow via the keras and tensorflow packages.