You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
89 lines
2.3 KiB
Plaintext
89 lines
2.3 KiB
Plaintext
7 years ago
|
{
|
||
|
"cells": [
|
||
|
{
|
||
|
"cell_type": "markdown",
|
||
|
"metadata": {},
|
||
|
"source": [
|
||
|
"# Sentiment Classification & How To \"Frame Problems\" for a Neural Network\n",
|
||
|
"\n",
|
||
|
"by Andrew Trask\n",
|
||
|
"\n",
|
||
|
"- **Twitter**: @iamtrask\n",
|
||
|
"- **Blog**: http://iamtrask.github.io"
|
||
|
]
|
||
|
},
|
||
|
{
|
||
|
"cell_type": "markdown",
|
||
|
"metadata": {},
|
||
|
"source": [
|
||
|
"### What You Should Already Know\n",
|
||
|
"\n",
|
||
|
"- neural networks, forward and back-propagation\n",
|
||
|
"- stochastic gradient descent\n",
|
||
|
"- mean squared error\n",
|
||
|
"- and train/test splits\n",
|
||
|
"\n",
|
||
|
"### Where to Get Help if You Need it\n",
|
||
|
"- Re-watch previous Udacity Lectures\n",
|
||
|
"- Leverage the recommended Course Reading Material - [Grokking Deep Learning](https://www.manning.com/books/grokking-deep-learning) (40% Off: **traskud17**)\n",
|
||
|
"- Shoot me a tweet @iamtrask\n",
|
||
|
"\n",
|
||
|
"\n",
|
||
|
"### Tutorial Outline:\n",
|
||
|
"\n",
|
||
|
"- Intro: The Importance of \"Framing a Problem\"\n",
|
||
|
"\n",
|
||
|
"\n",
|
||
|
"- Curate a Dataset\n",
|
||
|
"- Developing a \"Predictive Theory\"\n",
|
||
|
"- **PROJECT 1**: Quick Theory Validation\n",
|
||
|
"\n",
|
||
|
"\n",
|
||
|
"- Transforming Text to Numbers\n",
|
||
|
"- **PROJECT 2**: Creating the Input/Output Data\n",
|
||
|
"\n",
|
||
|
"\n",
|
||
|
"- Putting it all together in a Neural Network\n",
|
||
|
"- **PROJECT 3**: Building our Neural Network\n",
|
||
|
"\n",
|
||
|
"\n",
|
||
|
"- Understanding Neural Noise\n",
|
||
|
"- **PROJECT 4**: Making Learning Faster by Reducing Noise\n",
|
||
|
"\n",
|
||
|
"\n",
|
||
|
"- Analyzing Inefficiencies in our Network\n",
|
||
|
"- **PROJECT 5**: Making our Network Train and Run Faster\n",
|
||
|
"\n",
|
||
|
"\n",
|
||
|
"- Further Noise Reduction\n",
|
||
|
"- **PROJECT 6**: Reducing Noise by Strategically Reducing the Vocabulary\n",
|
||
|
"\n",
|
||
|
"\n",
|
||
|
"- Analysis: What's going on in the weights?"
|
||
|
]
|
||
|
}
|
||
|
],
|
||
|
"metadata": {
|
||
|
"anaconda-cloud": {},
|
||
|
"kernelspec": {
|
||
|
"display_name": "Python [default]",
|
||
|
"language": "python",
|
||
|
"name": "python3"
|
||
|
},
|
||
|
"language_info": {
|
||
|
"codemirror_mode": {
|
||
|
"name": "ipython",
|
||
|
"version": 3
|
||
|
},
|
||
|
"file_extension": ".py",
|
||
|
"mimetype": "text/x-python",
|
||
|
"name": "python",
|
||
|
"nbconvert_exporter": "python",
|
||
|
"pygments_lexer": "ipython3",
|
||
|
"version": "3.5.2"
|
||
|
}
|
||
|
},
|
||
|
"nbformat": 4,
|
||
|
"nbformat_minor": 1
|
||
|
}
|