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# Installation instructions for the TensorFlow workshop | ||
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## Install Conda + Python 3 to use as your local virtual environment | ||
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Anaconda is a Python distribution that includes a large number of standard numeric and scientific computing packages. Anaconda uses a package manager called "conda" that has its own environment system similar to Virtualenv. | ||
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Install the version of Conda that **uses Python 3.5** by default. Follow the instructions [here](https://www.continuum.io/downloads). The [miniconda version](http://conda.pydata.org/miniconda.html) should suffice. | ||
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## Install TensorFlow into a Conda environment | ||
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Follow the instructions [on the TensorFlow site](https://www.tensorflow.org/versions/r0.8/get_started/os_setup.html#anaconda-environment-installation) to create a Conda environment, *activate* it, and use pip to install TensorFlow within it. When following these instructions, be sure to use the Python 3 variant for both environment creation and in grabbing the TensorFlow .whl file. | ||
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Remember to activate this environment in all the terminal windows you use during this workshop. | ||
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## Install some Python packages | ||
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With your conda environment activated, install the following packages: | ||
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```sh | ||
$ conda install numpy | ||
$ conda install scipy | ||
$ pip install sklearn | ||
$ conda install matplotlib | ||
$ conda install jupyter | ||
``` | ||
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## Download data files for the workshop exercises | ||
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At various stages in this workshop, we'll have you download some data files. For convenience, we list them here: | ||
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https://storage.googleapis.com/oscon-tf-workshop-materials/saved_word2vec_model.zip | ||
https://storage.googleapis.com/oscon-tf-workshop-materials/processed_reddit_data/reddit_post_title_words.zip | ||
https://storage.googleapis.com/oscon-tf-workshop-materials/processed_reddit_data/news_aww/reddit_data.zip | ||
https://storage.googleapis.com/oscon-tf-workshop-materials/learned_word_embeddings/reddit_embeds.zip | ||
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(Thanks to [reddit](https://www.reddit.com/), for allowing us to use some post data for a training corpus.) | ||
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## Optional: Clone/Download the TensorFlow repo from GitHub | ||
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We'll be looking at some examples based on code in the tensorflow repo. While it's not necessary, you might want to clone or download it [here](https://github.com/tensorflow/tensorflow), or grab the 0.8 release [here](https://github.com/tensorflow/tensorflow/releases). | ||
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## Optional: Download Kubernetes, and set up a Google Cloud Platform account as necessary | ||
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In one section of the workshop, we'll look at running the TensorFlow distributed runtime on a [Kubernetes](http://kubernetes.io/) cluster. | ||
Kubernetes is Google's open-source container orchestration framework. It provides a useful framework to run microservice-based apps. | ||
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If you want to play along, create a Google Cloud Platform account and project ahead of time -- start with the 'try it free' button on [this page](https://cloud.google.com/) if you don't already have an account. | ||
(Alternately, understand how to stand up a Kubernetes cluster on some other cloud provider). | ||
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Then, download and install the [latest Kubernetes release](https://github.com/kubernetes/kubernetes/releases). | ||
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# TensorFlow workshop materials | ||
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This repo contains materials for use in a TensorFlow workshop. | ||
The accompanying slides are [here](xxx). | ||
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Contributions are not currently accepted. This is not an official Google product. | ||
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This document points to more information for each step in the workshop. | ||
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- [Installation](INSTALL.md) | ||
- [Building a small starter TensorFlow graph](workshop_sections/starter_tf_graph/README.md) | ||
- [Introducing word2vec](workshop_sections/intro_word2vec/README.md) | ||
- [The TensorFlow distributed runtime on Kubernetes](workshop_sections/tensorkubes/README.md) | ||
- [A less basic version of word2vec](workshop_sections/word2vec_optimized/README.md) | ||
- [Using convolutional NNs for text classification, and TensorBoard](workshop_sections/cnn_text_classification/README.md#using-convolutional-nns-for-text-classification-and-tensorboard) | ||
- [Using convolutional NNs for text classification, part II: using learned word embeddings](workshop_sections/cnn_text_classification/README.md#using-convolutional-nns-for-text-classification-part-ii-using-learned-word-embeddings) | ||
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Thanks to Denny Britz for this code: [https://github.com/dennybritz/cnn-text-classification-tf](https://github.com/dennybritz/cnn-text-classification-tf), which we adapted for some of the workshop sections. | ||
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Thanks also to [reddit](https://www.reddit.com/), for allowing us to use some post data for a training corpus. |
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This directory holds instructions for each of the workshop sections. | ||
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- [Building a small starter TensorFlow graph](starter_tf_graph/README.md) | ||
- [Introducing word2vec](intro_word2vec/README.md) | ||
- [The TensorFlow distributed runtime on Kubernetes](tensorkubes/README.md) | ||
- [A less basic version of word2vec](word2vec_optimized/README.md) | ||
- [Using convolutional NNs for text classification, and TensorBoard](cnn_text_classification/README.md#using-convolutional-nns-for-text-classification-and-tensorboard) | ||
- [Using convolutional NNs for text classification, part II: using learned word embeddings](cnn_text_classification/README.md#using-convolutional-nns-for-text-classification-part-ii-using-learned-word-embeddings) | ||
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