updated schedule

README.md

@@ -320,18 +320,18 @@ Recommended prereading: Chapters 1-2 (linear algebra) and chapter 3 (statistics)
 ###  Week 39 September 27- October 1
 - Lab Wednesday: Work on  Project 1
 - Lecture Thursday: Gradient Optimization methods
-- Lecture Friday:  Gradient methods and Deep Learning and Neural Networks
+- Lecture Friday:  Gradient methods
 
 - Reading recommendations:
   - See lecture notes for week 39 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.
-  - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4
+
 
 
 ###  Week 40 October 4-8
-- Lab Wednesday: Wrap up project 1 and start project 2
+- Lab Wednesday: Wrap up project 1
 - Lecture Thursday: Writing a feed-forward Neural Network code for regression and classification
-- Lecture Friday:  Deep Learning and TensorFlow and Keras
+- Lecture Friday:  Deep Learning and Neural Networks
 - Reading recommendations:
   - See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4

doc/LectureNotes/_build/html/_sources/schedule.md

@@ -90,18 +90,18 @@ For the reading assignments we use the following abbreviations:
 ###  Week 39 September 27- October 1
 - Lab Wednesday: Work on  Project 1
 - Lecture Thursday: Gradient Optimization methods
-- Lecture Friday:  Gradient methods and Deep Learning and Neural Networks
+- Lecture Friday:  Gradient methods
 
 - Reading recommendations:
   - See lecture notes for week 39 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.
-  - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4
+
 
 
 ###  Week 40 October 4-8
-- Lab Wednesday: Wrap up project 1 and start project 2
+- Lab Wednesday: Wrap up project 1
 - Lecture Thursday: Writing a feed-forward Neural Network code for regression and classification
-- Lecture Friday:  Deep Learning and TensorFlow and Keras
+- Lecture Friday:  Deep Learning and Neural Networks
 - Reading recommendations:
   - See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4

doc/LectureNotes/_build/html/schedule.html

@@ -514,12 +514,11 @@
 <ul class="simple">
 <li><p>Lab Wednesday: Work on  Project 1</p></li>
 <li><p>Lecture Thursday: Gradient Optimization methods</p></li>
-<li><p>Lecture Friday:  Gradient methods and Deep Learning and Neural Networks</p></li>
+<li><p>Lecture Friday:  Gradient methods</p></li>
 <li><p>Reading recommendations:</p>
 <ul>
 <li><p>See lecture notes for week 39 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>
 <li><p>For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.</p></li>
-<li><p>For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4</p></li>
 </ul>
 </li>
 </ul>
@@ -527,9 +526,9 @@
 <div class="section" id="week-40-october-4-8">
 <h3>Week 40 October 4-8<a class="headerlink" href="#week-40-october-4-8" title="Permalink to this headline">¶</a></h3>
 <ul class="simple">
-<li><p>Lab Wednesday: Wrap up project 1 and start project 2</p></li>
+<li><p>Lab Wednesday: Wrap up project 1</p></li>
 <li><p>Lecture Thursday: Writing a feed-forward Neural Network code for regression and classification</p></li>
-<li><p>Lecture Friday:  Deep Learning and TensorFlow and Keras</p></li>
+<li><p>Lecture Friday:  Deep Learning and Neural Networks</p></li>
 <li><p>Reading recommendations:</p>
 <ul>
 <li><p>See lecture notes for week 40 at <a class="reference external" href="https://compphysics.github.io/MachineLearning/doc/web/course.html">https://compphysics.github.io/MachineLearning/doc/web/course.html</a>.</p></li>

doc/LectureNotes/schedule.md

@@ -90,18 +90,18 @@ For the reading assignments we use the following abbreviations:
 ###  Week 39 September 27- October 1
 - Lab Wednesday: Work on  Project 1
 - Lecture Thursday: Gradient Optimization methods
-- Lecture Friday:  Gradient methods and Deep Learning and Neural Networks
+- Lecture Friday:  Gradient methods
 
 - Reading recommendations:
   - See lecture notes for week 39 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For a good discussion on gradient methods, see Goodfellow et al section 4.3-4.5 and chapter 8. We will come back to the latter chapter in our discussion of Neural networks as well.
-  - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4
+
 
 
 ###  Week 40 October 4-8
-- Lab Wednesday: Wrap up project 1 and start project 2
+- Lab Wednesday: Wrap up project 1
 - Lecture Thursday: Writing a feed-forward Neural Network code for regression and classification
-- Lecture Friday:  Deep Learning and TensorFlow and Keras
+- Lecture Friday:  Deep Learning and Neural Networks
 - Reading recommendations:
   - See lecture notes for week 40 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
   - For neural networks we recommend Goodfellow et al chapters 6 and 7 and Bishop 5.1-5.4