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Simplify your deep learning implementation by using these tools. Based on Tensorflow.js

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Simple Tensorflow for NodeJS

Ready to use algorithms to train your own models with Tensorflow for NodeJS.

Scripts

Basic scripts:

# Install dependencies
npm install # Important: do NOT use yarn as it doesn't support npm_config variables!!!

# Build app
npm run build

Train model:

npm run model:train --name=NAME_OF_MODEL

Example model training

  1. Copy cars.json from src/models/examples/cars into models folder in your project root
  2. Run npm run model:train --name=example/cars
  3. Get familiar with the tabular data in the output

Output explanation:

You should notice 6 columns:

  • (index) - just a row number
  • Acc - car acceleration - first input data
  • Weight - car's weight in lbs - seconds input data
  • HP - car's horsepower - output record from the test data
  • HP (pred) - car's horsepower - predicted by your AI model
  • Diff - difference between HP and HP (pred)

It's not perfect. Should I worry?

In this case - definitely not! First of all the model is trained only on 320 records. 80 were used to test model accuracy. Secondly, we can see model isn't overtrained which is a good sign Lastly, the difference between HP and HP (pred) is not that big. It's just ~12-15 on average.

Imagine you have a car, the has 2074lbs weight and accelerates to 100mph in 19 seconds. Is it possible to predict its actual horsepower? Definitely not! In this case the model predicts it as similar as human would so we can consider this as an expected result.

TODO:

  1. Read CSV
  2. Simplify code more and more
  3. Add classification algorithms (SVM and KNN)
  4. Add Image recognition algorithms (using CNN)
  5. Add NLP algorithms (probably using RNN)
  6. Add more examples

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Simplify your deep learning implementation by using these tools. Based on Tensorflow.js

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