Merge branch 'master' of github.com:dssg/MLforPublicPolicy

dssg · Apr 23, 2019 · f5b93fe · f5b93fe
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diff --git a/Assignments/Homework 2 – Machine Learning Pipeline.pdf b/Assignments/Homework 2 – Machine Learning Pipeline.pdf
diff --git a/Assignments/Homework 3 - Improving the Pipeline.pdf b/Assignments/Homework 3 - Improving the Pipeline.pdf
diff --git a/Lectures/Lecture 03 - Machine Learning Process.pptx b/Lectures/Lecture 03 - Machine Learning Process.pptx
diff --git a/Lectures/Lecture 04 - Supervised Learning 1.pptx b/Lectures/Lecture 04 - Supervised Learning 1.pptx
diff --git a/Lectures/Lecture 05 - Supervised Learning 2.pptx b/Lectures/Lecture 05 - Supervised Learning 2.pptx
diff --git a/Lectures/Lecture 06 - Supervised Learning 3.pptx b/Lectures/Lecture 06 - Supervised Learning 3.pptx
diff --git a/Lectures/Lecture 07 - Supervised Learning 4.pptx b/Lectures/Lecture 07 - Supervised Learning 4.pptx
diff --git a/Lectures/Lecture 08 - Evaluation.pptx b/Lectures/Lecture 08 - Evaluation.pptx
diff --git a/README.md b/README.md
@@ -6,7 +6,7 @@ The current version of this course is being offered in Spring 2019 at the Univer
 
 
 #### Textbooks:
-There are two recommended textbooks:
+There is no book that covers this topic well. We will use two textbooks as recommended and augment through class lectures:
 1. Data Science for Business. Foster Provost and Tom Fawcett
 2. Machine Learning: The Art and Science of Algorithms that Make Sense of Data. Peter Flach
 
@@ -18,7 +18,7 @@ This is the repository for the Machine Learning for Public Policy class at the U
 * [Project Guidelines](Project/)
 * [Practical Tools and Tips](Practical%20CTips/)
 
-You can also take a look at the [Syllabus](syllabus.pdf) as well as the [weekly schedule](schedule.pdf).
+You can also take a look at the [Syllabus](syllabus.pdf) as well as the [weekly schedule](schedule.png?raw=true).
 
 ## Schedule