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+[X] README.md included
+[X] Slides included
+[X] Code included
+
+## Clean Code:
+
+- Code follows PEP-8
+- Very readable and easy to follow
+- Create a separate notebook or file for scraping and another for cleaning your data. For future projects try creating functions. These functions can then be 
+  placed in py files. Then you can call the function from your jupyter notebook. 
+
+## Good Documentation:
+
+- In your README.md, provide a clear scope and analysis, methodology, data science methods used, and summary of your findings.
+- Markdown cell at beginning of .ipynb explains scope and analyis
+- Inline code comments were used, but include them where help and necessary. For instance, comment/describe the "next gen feature" 
+
+
+## Proper Data Science:
+
+- Code demonstrates good Linear Regression understanding. Great thought process to try modeling with regularization.
+- Consider log transforming your target
+- Good visualizations -- not too much info, clear and interpretable. Love the busiest stations highlighted in orange on gray, very effective way to highlight relevant info.
+
+## Comments:
+
+- Good job on project 2! :)
+- Love the approach/project design. Very clear and concise
+- Nice visualizations and analysis
+- Be sure to include a "results" section in your README in the future.