Add Fine-tune RidgeClassifier example notebook

Adds a notebook that trains a RidgeClassifier that predicts
species based on image embeddings created by BioCLIP. The
RidgeClassifier logic is simplified from init_svc() in
https://github.com/samuelstevens/biobench by @samuelstevens.

Part of issue #76.

Co-authored-by: Samuel Stevens <samuel.robert.stevens@gmail.com>

docs/python-tutorial.md

@@ -143,6 +143,13 @@ As can be seen from comparing the confusion matrices, fine-tuning an SVM classif
 
 This work is based on code from [biobench](https://github.com/samuelstevens/biobench). 
 
+### Fine-tune with RidgeClassifier
+[FineTuneRidgeClassifier.ipynb](https://github.com/Imageomics/pybioclip/blob/main/examples/FineTuneRidgeClassifier.ipynb) Fine-tunes  BioCLIP by combining an [RidgeClassifier](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html) with BioCLIP image embeddings. <a target="_blank" href="https://colab.research.google.com/github/Imageomics/pybioclip/blob/main/examples/FineTuneRidgeClassifier.ipynb">
+  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
+As can be seen from comparing the confusion matrices, fine-tuning a RidgeClassifier classifier on BioCLIP image embeddings may yield better results than using BioCLIP in "zero-shot mode", i.e., predicting on a list of custom labels.
+
+This work is based on code from [biobench](https://github.com/samuelstevens/biobench). 
+
 ## PIL Images
 The predict() functions used in all the examples above allow passing a list of paths or a list of [PIL Images](https://pillow.readthedocs.io/en/stable/reference/Image.html).
 When a list of PIL images is passed the index of the image will be filled in for `file_name`. This is because PIL images may not have an associated file name.