regression tutorial 2 added

README.rst

@@ -296,6 +296,11 @@ It consists of interactive notebooks with complete explanations that can get you
         :alt: Open In Colab
         :target: https://colab.research.google.com/github/jeshraghian/snntorch/blob/master/examples/tutorial_regression_1.ipynb
 
+   * - `Regression: Part II - Regression-based Classification with Recurrent LIF Neurons <https://snntorch.readthedocs.io/en/latest/tutorials/tutorial_regression_2.html>`_
+     - .. image:: https://colab.research.google.com/assets/colab-badge.svg
+        :alt: Open In Colab
+        :target: https://colab.research.google.com/github/jeshraghian/snntorch/blob/master/examples/tutorial_regression_2.ipynb
+
    * - `Accelerating snnTorch on IPUs <https://snntorch.readthedocs.io/en/latest/tutorials/tutorial_ipu_1.html>`_
      -       —
 

docs/tutorials/tutorial_regression_1.rst

@@ -5,7 +5,7 @@ Regression with SNNs: Part I
 Learning Membrane Potentials with LIF Neurons
 ---------------------------------------------
 
-Tutorial written by Alexander Henkes (`ORCID <https://orcid.org/0000-0003-4615-9271>`_) and Jason K. Eshraghian (`ncg.ucsc.edu <https://ncg.ucsc.edu1>`_)
+Tutorial written by Alexander Henkes (`ORCID <https://orcid.org/0000-0003-4615-9271>`_) and Jason K. Eshraghian (`ncg.ucsc.edu <https://ncg.ucsc.edu>`_)
 
 
 .. image:: https://colab.research.google.com/assets/colab-badge.svg
@@ -43,11 +43,8 @@ An overview of the regression tutorial series:
 
 -  Part I (this tutorial) will train the membrane potential of a LIF
    neuron to follow a given trajectory over time.
--  Part II will improve upon these results by using a more complex
-   spiking LSTM network instead.
--  Part III will use LIF neurons with recurrent feedback to train the
-   firing time of a neuron.
-
+-  Part II will use LIF neurons with recurrent feedback to perform classification using regression-based loss functions
+-  Part III will use a more complex spiking LSTM network instead to train the firing time of a neuron.
 
 ::