Questions

Here are some questions to review what we have learned in the chapter:

1. Which one of the following is not true about machine learning?
   1. Supervised learning needs labeled data to train models.
   2. Unsupervised learning tries to find outliers in data.
   3. The agent in reinforced learning interacts with the environment to learn.
   4. Reinforced learning is superior to others at detecting patterns in data.
2. Which one of the following is not a step in the tinyML pipeline?
   1. Data collection and pre-processing
   2. Training the model on an IoT device
   3. Optimizing the model for deployment
   4. Running inference on an IoT device
3. Which technique makes an ML model small enough to fit into the memory of an IoT device?
   1. Training
   2. Quantization
   3. Overfitting
   4. Validation
4. With TFLM, we can:
   1. Optimize a TensorFlow model...