目录 Preface 1. Introduction Embedded Devices Changing Landscape 2. Getting Started Who Is This Book Aimed At? What Hardware Do You Need? What Software Do You Need? What Do We Hope You'll Learn? 3. Getting Up to Speed on Machine Learning What Machine Learning Actually Is The Deep Learning Workflow Decide on a Goal Collect a Dataset Design a Model Architecture Train the Model Convert the Model Run Inference Evaluate and Troubleshoot Wrapping Up 4. The "Hello World" of TinyML: Building and Training a Model What We're Building Our Machine Learning Toolchain Python and Jupyter Notebooks Google Colaboratory TensorFlow and Keras Building Our Model Importing Dependencies Generating Data Splitting the Data Defining a Basic Model Training Our Model Training Metrics Graphing the History Improving Our Model Testing Converting the Model for TensorFlow Lite Converting to a C File Wrapping Up 5. The "Hello World" of TinyMt: Builfling an Application Walking Through the Tests Including Dependencies Setting Up the Test Getting Ready to Log Data Mapping Our Model Creating an AllOpsResolver Defining a Tensor Arena Creating an Interpreter Inspecting the Input Tensor Running Inference on an Input
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