vault backup: 2023-12-27 21:56:22

Affected files:
.obsidian/graph.json
.obsidian/workspace-mobile.json
.obsidian/workspace.json
Languages/Spanish/Spanish.md
STEM/AI/Classification/Classification.md
STEM/AI/Classification/Decision Trees.md
STEM/AI/Classification/Logistic Regression.md
STEM/AI/Classification/Random Forest.md
STEM/AI/Classification/Supervised/SVM.md
STEM/AI/Classification/Supervised/Supervised.md
STEM/AI/Neural Networks/Activation Functions.md
STEM/AI/Neural Networks/CNN/CNN.md
STEM/AI/Neural Networks/CNN/GAN/DC-GAN.md
STEM/AI/Neural Networks/CNN/GAN/GAN.md
STEM/AI/Neural Networks/Deep Learning.md
STEM/AI/Neural Networks/Properties+Capabilities.md
STEM/AI/Neural Networks/SLP/Perceptron Convergence.md

AI/Classification/Classification.md

@@ -1,6 +1,7 @@
 ---
 tags:
   - ai
+  - classification
 ---
 *Given an observation, determine one class from a set of classes that best explains the observation*
 

AI/Classification/Decision Trees.md

@@ -1,6 +1,7 @@
 ---
 tags:
   - ai
+  - classification
 ---
 - Flowchart like design
 - Iterative decision making

AI/Classification/Logistic Regression.md

@@ -1,6 +1,7 @@
 ---
 tags:
   - ai
+  - classification
 ---
 “hello world”
 Related to naïve bayes

AI/Classification/Random Forest.md

@@ -1,4 +1,5 @@
 ---
 tags:
+  - classification
 ---
 “Almost always the second best algorithm for any shallow ML task”

AI/Classification/Supervised/SVM.md

@@ -1,6 +1,7 @@
 ---
 tags:
   - ai
+  - classification
 ---
 [Towards Data Science: SVM](https://towardsdatascience.com/support-vector-machines-svm-c9ef22815589)
 [Towards Data Science: SVM an overview](https://towardsdatascience.com/https-medium-com-pupalerushikesh-svm-f4b42800e989)

AI/Classification/Supervised/Supervised.md

@@ -1,6 +1,7 @@
 ---
 tags:
   - ai
+  - classification
 ---
 
 # Gaussian Classifier

AI/Neural Networks/Activation Functions.md

@@ -66,7 +66,7 @@ Rectilinear
 ![relu](../../img/relu.png)
 
 # SoftMax
-- Output is per-class vector of likelihoods
+- Output is per-class vector of likelihoods #classification 
 	- Should be normalised into probability vector
 
 ## AlexNet

AI/Neural Networks/CNN/CNN.md

@@ -25,8 +25,8 @@ tags:
 
 # As a Descriptor
 - Most powerful as a deeply learned feature extractor
-- [Dense](../MLP/MLP.md) classifier at the end isn't fantastic
-	- Use SVM to classify prior to penultimate layer
+- [Dense](../MLP/MLP.md) [classifier](../../Classification/Classification.md) at the end isn't fantastic
+	- Use SVM to classify prior to penultimate layer #classification 
 
 ![cnn-descriptor](../../../img/cnn-descriptor.png)
 

AI/Neural Networks/CNN/GAN/DC-GAN.md

@@ -68,7 +68,7 @@ $$J^{(G)}=-J^{(D)}$$
 		- Input random noise
 - Iteratively improves visual feasibility
 	- Different to [FCN](../FCN/FCN.md)
-- Discriminator is a task specific classifier
+- Discriminator is a task specific classifier #classification 
 - Difficult to train over diverse footage
 	- Mixing concepts doesn't work
 	- Single category/class

AI/Neural Networks/CNN/GAN/GAN.md

@@ -18,7 +18,7 @@ tags:
 - Synthesise 'fake' images
 - From noise
 ## Discriminator, D
-- Discriminator is a classifier
+- Discriminator is a classifier #classification 
 	- Is image fake or real
 
 ![gan-arch](../../../../img/gan-arch.png)

AI/Neural Networks/Deep Learning.md

@@ -3,6 +3,7 @@ tags:
   - ai
 ---
 ![deep-digit-classification](../../img/deep-digit-classification.png)
+#classification 
 
 OCR [Classification](../Classification/Classification.md)
 

AI/Neural Networks/Properties+Capabilities.md

@@ -88,7 +88,7 @@ tags:
 	- Number of connections becomes prohibitively large
 2. Invariance by Training
 	- Train on different views/transformations
-		- Take advantage of inherent pattern classification abilities
+		- Take advantage of inherent pattern #classification abilities
 	- Training for invariance for one object is not necessarily going to train other classes for invariance
 	- Extra load on network to do more training
 		- Exacerbated with high dimensionality

AI/Neural Networks/SLP/Perceptron Convergence.md

@@ -1,6 +1,7 @@
 ---
 tags:
   - ai
+  - classification
 ---
 Error-Correcting Perceptron Learning