update week43

doc/src/week43/week43.do.txt

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-TITLE: Week 43: Deep Learning: Recurrent Neural Networks and other Deep Learning Methods. Principal Component analysis
+ATITLE: Week 43: Deep Learning: Recurrent Neural Networks and other Deep Learning Methods. Principal Component analysis
 AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} at Department of Physics, University of Oslo & Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University
 DATE: today
 
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 ===== Plans for week 43 =====
 
-* Thursday: Summary of Convolutional Neural Networks from week 42 and Recurrent Neural Networks
-* Friday: Recurrent Neural Networks and other Deep Learning methods such as Generalized Adversarial Neural Networks. Start discussing Principal component analysis
+* Thursday: Convolutional Neural Networks, basic elements and 
+* Friday: Recurrent Neural Networks and other Deep, Generalized Adversarial Neural Networ and autoencoders
 
 
 
@@ -29,12 +29,6 @@ DATE: today
 * Aurelien Geron, chapter 14 on RNNs.
 
 
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-===== Summary on Deep Learning Methods =====
-
-We have studied fully connected neural networks (also called artifical nueral networks) and convolutional neural networks (CNNs).
-
-The first type of deep learning networks work very well on homogeneous and structured input data while CCNs are normally tailored to recognizing images.
 
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 ===== CNNs in brief =====