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89 lines
2.3 KiB
Plaintext
89 lines
2.3 KiB
Plaintext
{
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"# Sentiment Classification & How To \"Frame Problems\" for a Neural Network\n",
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"\n",
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"by Andrew Trask\n",
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"\n",
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"- **Twitter**: @iamtrask\n",
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"- **Blog**: http://iamtrask.github.io"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"### What You Should Already Know\n",
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"\n",
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"- neural networks, forward and back-propagation\n",
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"- stochastic gradient descent\n",
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"- mean squared error\n",
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"- and train/test splits\n",
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"\n",
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"### Where to Get Help if You Need it\n",
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"- Re-watch previous Udacity Lectures\n",
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"- Leverage the recommended Course Reading Material - [Grokking Deep Learning](https://www.manning.com/books/grokking-deep-learning) (40% Off: **traskud17**)\n",
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"- Shoot me a tweet @iamtrask\n",
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"\n",
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"\n",
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"### Tutorial Outline:\n",
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"\n",
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"- Intro: The Importance of \"Framing a Problem\"\n",
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"\n",
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"\n",
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"- Curate a Dataset\n",
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"- Developing a \"Predictive Theory\"\n",
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"- **PROJECT 1**: Quick Theory Validation\n",
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"\n",
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"\n",
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"- Transforming Text to Numbers\n",
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"- **PROJECT 2**: Creating the Input/Output Data\n",
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"\n",
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"\n",
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"- Putting it all together in a Neural Network\n",
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"- **PROJECT 3**: Building our Neural Network\n",
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"\n",
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"\n",
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"- Understanding Neural Noise\n",
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"- **PROJECT 4**: Making Learning Faster by Reducing Noise\n",
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"\n",
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"\n",
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"- Analyzing Inefficiencies in our Network\n",
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"- **PROJECT 5**: Making our Network Train and Run Faster\n",
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"\n",
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"\n",
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"- Further Noise Reduction\n",
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"- **PROJECT 6**: Reducing Noise by Strategically Reducing the Vocabulary\n",
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"\n",
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"\n",
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"- Analysis: What's going on in the weights?"
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]
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}
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],
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