diff --git a/images/AI.svg b/images/AI.svg new file mode 100644 index 0000000..04ee983 --- /dev/null +++ b/images/AI.svg @@ -0,0 +1,14 @@ + + + diff --git a/index.html b/index.html index 59bdb0d..eee798c 100644 --- a/index.html +++ b/index.html @@ -1,13 +1,39 @@
+Gert Cauwenberghs
+CLSP, ECE Dept.
+Johns Hopkins University
+Baltimore, MD 21218
+ ger@jhu.edu +Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum
+Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
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+ Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions.[1] Recently, artificial neural networks have been able to surpass many previous approaches in performance
+As a scientific endeavor, machine learning grew out of the quest for artificial intelligence (AI). In the early days of AI as an academic discipline, some researchers were interested in having machines learn from data. They attempted to approach the problem with various symbolic methods, as well as what were then termed "neural networks"; these were mostly perceptrons and other models that were later found to be reinventions of the generalized linear models of statistics.[23] Probabilistic reasoning was also employed, especially in automated medical diagnosis.
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