This is an e2e TensorFlow workshop from model training using Keras API all the way to visualization using TensorFlow.js
User will need to complete exercises (.ipynb files) under py/ folder. Reference implementation could be found from /py/solutions folder.
- Prepare environment
- For Windows users, download and install ANaconda with either Python 2 or Python 3
- For Linux/Mac users, you should already have Python installed
- Install dependencies
pip install -r requirements.txt- If you're facing connectivity issues, please use
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt
- Visualize the initial model in browser
- For Python 2 users,
python -m SimpleHTTPServer - For Python 3 users,
python -m http.server - Open localhost:8080 in your browser
- Most of the predictions are wrong (red) because the model is doing random guess
- For Python 2 users,
- Coding
- Use jupyter notebook to complete an exercise and generate a model
- Convert the mdoel to TF JS format
- For windows users,
convert.bat PATH_TO_THE_H5_FILE - For Linux/Mac users,
convert.sh PATH_TO_THE_H5_FILE
- For windows users,
- Visualize the model in browser
- For Python 2 users,
python -m SimpleHTTPServer - For Python 3 users,
python -m http.server - Open localhost:8080 in your browser
- Most of the predictions should be correct (green) now
- For Python 2 users,