October 2017
Intermediate to advanced
330 pages
7h 7m
English
Content preview from Python Deep Learning Cookbook
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Programming Environments, GPU Computing, Cloud Solutions, and Deep Learning Frameworks
This chapter focuses on technical solutions to set up popular deep learning frameworks. First, we provide solutions to set up a stable and flexible environment on local machines and with cloud solutions. Next, all popular Python deep learning frameworks are discussed in detail:
- Setting up a deep learning environment
- Launching an instance on Amazon Web Services (AWS)
- Launching an instance on Google Cloud Platform (GCP)
- Installing CUDA and cuDNN
- Installing Anaconda and libraries
- Connecting with Jupyter Notebook on a server
- Building state-of-the-art, production-ready models with TensorFlow
- Intuitively building networks with Keras
- Using PyTorch's dynamic computation ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.