# LSTM-Sentiment-Analysis

**Repository Path**: swert/LSTM-Sentiment-Analysis

## Basic Information

- **Project Name**: LSTM-Sentiment-Analysis
- **Description**: test
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2017-06-30
- **Last Updated**: 2020-12-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Sentiment Analysis with LSTMs

This repository contains the iPython notebook and training data to accompany the O'Reilly tutorial on sentiment analysis with LSTMs in Tensorflow (insert link later). See the original tutorial (insert link later) to run this code in a pre-built environment on O'Reilly's servers with cell-by-cell guidance, or run these files on your own machine. There is also another file called `Pre-Trained LSTM.ipynb` which allows you to input your own text, and see the output of the trained network. 

## Downloading Data
Before running the notebook, you'll first need to download all data we'll be using. This data is located in the `models.tar.gz` and `training_data.tar.gz` tarballs. We will extract these into the same directory as `Oriole LSTM.ipynb`. As always, the first step is to clone the repository.
   ```bash
   git clone https://github.com/adeshpande3/LSTM-Sentiment-Analysis.git
   ```
Next, we will navigate to the newly created directory and run the following commands. 
   ```bash
   tar -xvzf models.tar.gz
   tar -xvzf training_data.tar.gz
   ```

## Requirements and Installation
In order to run [the iPython notebook](Oriole-LSTM.ipynb), you'll need the following libraries. 

* **[TensorFlow](https://www.tensorflow.org/install/) version 1.0 or later**
* [NumPy](https://docs.scipy.org/doc/numpy/user/install.html)
* [Jupyter](https://jupyter.readthedocs.io/en/latest/install.html)
* [matplotlib](https://matplotlib.org/)

### Installing Anaconda Python and TensorFlow
The easiest way to install TensorFlow as well as NumPy, Jupyter, and matplotlib is to start with the Anaconda Python distribution.

1. Follow the [installation instructions for Anaconda Python](https://www.continuum.io/downloads). **We recommend using Python 3.6.**

2. Follow the platform-specific [TensorFlow installation instructions](https://www.tensorflow.org/install/). Be sure to follow the "Installing with Anaconda" process, and create a Conda environment named `tensorflow`.

3. If you aren't still inside your Conda TensorFlow environment, enter it by opening your terminal and typing
    ```bash
    source activate tensorflow
    ```

4. If you haven't done so already, download and unzip [this entire repository from GitHub](https://github.com/adeshpande3/LSTM-Sentiment-Analysis), either interactively, or by entering
    ```bash
    git clone https://github.com/adeshpande3/LSTM-Sentiment-Analysis
    ```

5. Use `cd` to navigate into the top directory of the repo on your machine

6. Launch Jupyter by entering
    ```bash
    jupyter notebook
    ```
    and, using your browser, navigate to the URL shown in the terminal output (usually http://localhost:8888/)