Update book1.html

book1.html

@@ -69,6 +69,15 @@ <h2><a id="endorsements"></a>Endorsements</h2>
       is a must-have for anyone interested in gaining a deep understanding of machine learning."
 	    -- <a href="https://www.microsoft.com/en-us/research/people/cmbishop/">Chris Bishop</a>,
 	Microsoft Research.
+
+	    <p>
+		    <li>
+	    "This book is a clear, concise, and rigorous introduction to the foundations of machine learning. 
+	    It beautifully bridges between the "traditional" topics and the more "modern" deep learning methods, 
+	    creating a unifying framework that contextualizes both of them. It's the book I recommend for people who are new to the 
+	    field and want to obtain a comprehensive view of the core principles and methods."
+			    -- <a href="https://ai.stanford.edu/~koller/">Daphne Koller</a>, Insitro/ Stanford.
+
 
 <p>
 	<li>
@@ -79,7 +88,7 @@ <h2><a id="endorsements"></a>Endorsements</h2>
 		that most of the figures  of the book have a link to the associated 
 		(python, JAX, tensorflow) code that is used to generate them,
 		often with comparisons between the different computational ways of solving the problems."
-		-- <a href="https://www.seas.harvard.edu/brenner/Home.html">Michael Brenner</a>, Harvard.
+		-- <a href="https://www.seas.harvard.edu/brenner/Home.html">Michael Brenner</a>, Harvard/ Google.
 
 	  <p>
 		  <li>