docs(compression): add MNIST compression tutorial (#3224)

Add a comprehensive Jupyter notebook tutorial demonstrating TFLM's
compression pipeline using the MNIST dataset. The tutorial covers weight
clustering with TensorFlow Model Optimization toolkit, post-training
quantization, and TFLM's LUT-based compression.

Update documentation to reference the new tutorial from the main README,
Python interpreter guide, and compression documentation.

BUG=#2636

Co-authored-by: Esun Kim <veblush@google.com>

Author: rkuester

README.md

@@ -101,6 +101,8 @@ The following resources may also be useful:
    * [Arm IP support](tensorflow/lite/micro/docs/arm.md)
  * [Software Emulation with Renode](tensorflow/lite/micro/docs/renode.md)
  * [Software Emulation with QEMU](tensorflow/lite/micro/docs/qemu.md)
+ * [Compression](tensorflow/lite/micro/docs/compression.md)
+   * [MNIST Compression Tutorial](tensorflow/lite/micro/compression/mnist_compression_tutorial.ipynb)
  * [Python Dev Guide](docs/python.md)
  * [Automatically Generated Files](docs/automatically_generated_files.md)
  * [Python Interpreter Guide](python/tflite_micro/README.md)

python/tflite_micro/README.md

@@ -157,6 +157,11 @@ print(tflm_interpreter.get_input_details(0))
 print(tflm_interpreter.get_output_details(0))
 ```
 
+### Tutorials
+
+For a complete end-to-end example using the Python interpreter for model compression:
+* [MNIST Compression Tutorial](../../tensorflow/lite/micro/compression/mnist_compression_tutorial.ipynb)
+
 ### Technical Details
 
 The Python interpreter uses [pybind11](https://github.com/pybind/pybind11) to