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@@ -16,7 +16,7 @@ Corrections or suggestions? Please file a [GitHub issue](https://github.com/jpha
## Lecture 1: Explainable Machine Learning Models
![Histogram, partial dependence, and ICE for a monotonic GBM and a credit card customer's most recent repayment status](/img/ebm.png)
-**Source:** [Simple Explainable Boosting Machine Example](https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/lecture_1_ebm_example.ipynb?flush_cache=true) (Jupyter)
+**Source:** [Simple Explainable Boosting Machine Example](https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/lecture_1_ebm_example.ipynb?flush_cache=true)
### Lecture 1 Class Materials
@@ -26,9 +26,9 @@ Corrections or suggestions? Please file a [GitHub issue](https://github.com/jpha
* [Primer on Technical Malpractice](https://docs.google.com/presentation/d/1cZeaoIp4cQsVY_gj2a5Pg7ygexepQZRS-ZEn6n2QqEU/edit?usp=sharing)
* [Whiteboard Notation](https://docs.google.com/presentation/d/1Axf9dizaE3XvGRelBHfsnAlMUPFuMExQ2WNVwQBKMrw/edit?usp=sharing)
* [Lecture Notes](tex/lecture_1.pdf)
-* [Assignment 1](assignments/tex/assignment_1.pdf)
+* [Assignment 1](assignments/tex/assignment_1.pdf):
* [Model evaluation notebook](https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/assignments/eval.ipynb)
- * [Full evaluations results](https://github.com/jphall663/GWU_rml/blob/master/assignments/model_eval_2022_06_13_09_47_08.csv)
+ * [Full evaluations results]()
* Software Examples:
* [Building from Penalized GLM to Monotonic GBM (simple)](https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/lecture_1.ipynb?flush_cache=true)
* [Building from Penalized GLM to Monotonic GBM](https://nbviewer.org/github/jphall663/interpretable_machine_learning_with_python/blob/master/glm_mgbm_gbm.ipynb?flush_cache=true)