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| README.md | ||
| train_hello_world_model.ipynb | ||
Hello World Training
This example shows how to train a 2.5 kB model to generate a sine wave.
Table of contents
Overview
- Dataset: Data is generated locally in the Jupyter Notebook.
- Dataset Type: Structured Data
- Deep Learning Framework: TensorFlow 2
- Language: Python 3.7
- Model Size: 2.5 kB
- Model Category: Regression
Training
Train the model in the cloud using Google Colaboratory or locally using a Jupyter Notebook.
 Google Colaboratory
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 Jupyter Notebook
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Estimated Training Time: 10 minutes.
Trained Models
| Download Link | hello_world.zip |
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The models directory in the above zip file can be generated by following the
instructions in the Training section above. It
includes the following 3 model files:
| Name | Format | Target Framework | Target Device |
|---|---|---|---|
model.pb |
Keras SavedModel | TensorFlow | Large-Scale/Cloud/Servers |
model.tflite (2.5 kB) |
Integer Only Quantized TFLite Model | TensorFlow Lite | Mobile Devices |
model.cc |
C Source File | TensorFlow Lite for Microcontrollers | Microcontrollers |
Model Architecture
The final model used to simulate a sine wave is displayed below. It is a simple feed forward deep neural network with 2 fully connected layers with ReLu activations and a final fully connected output layer with as shown below.
This image was derived from visualizing the 'model.tflite' file in Netron