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* Title..: Pluralsight Caffe2 Getting Started
* Date...: 28-09-2018
* Type...: Bookware
* Disks..: 19x15mb

Release notes:

Caffe2 is an open-source deep learning framework and
competitor to frameworks such as TensorFlow, Apache MXNet
and PyTorch. It's focus is on efficiency and works well with
constrained environments such as on mobile devices. In this
course, Caffe2: Getting Started, you'll learn the
fundamentals of building neural nets and working with
Caffe2, get introduced to the Caffe2 Model Zoo and see how
you can import models from PyTorch to Caffe2 using ONNX.
First, you'll discover the basic building blocks of Caffe2,
blobs and workspaces, nets and operators, and put those
together to build neural networks to perform tasks such as
regression and classification. Then, you'll get introduced
to common image pre-processing techniques and the Caffe2
Model Zoo which offers a wide variety of pre-trained models
for common use cases. Next, you'll focus on interoperability
between the PyTorch deep learning framework and Caffe2 using
ONNX, an open source framework for exporting models from one
framework to another. Last, you'll use ONNX to move a super-
resolution model from PyTorch to Caffe2. By the end of this
course, you should be comfortable building and executing
neural networks using Caffe2, using pre-trained models for
common tasks and using ONNX to move from one framework to
another.

More info:
https://www.pluralsight.com

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