commit c8cdc0b5737da02dfdba87e1b19fbb891b580963
parent c57ef08a9f4c81a260e650dc925d6ab3c3e4a707
Author: Andrew <andrewlaack1@gmail.com>
Date: Thu, 9 May 2024 20:23:56 -0500
Taking notes on ml
Diffstat:
18 files changed, 140 insertions(+), 7 deletions(-)
diff --git a/AnomalyDetection.md b/AnomalyDetection.md
@@ -0,0 +1,14 @@
+:ml:
+# Anomaly Detection
+
+ML CH1
+
+## Notes
+
+**Definition:** Anomaly detection is the task of detecting anomalous samples.
+
+A common example of this is unusual credit card transactions used to prevent fraud.
+
+This is also commonly used to detect manufacturing faults.
+
+These models are trained on normal data then when abnormal data is fed to it, it marks it as such.
diff --git a/Blender.md b/Blender.md
@@ -15,7 +15,10 @@ The default file format is FBX (Filmbox) which can be imported into [[Unity.md]]
[[Animation.md]]
[[KeyframeAnimation.md]]
[[SkeletalAnimation.md]]
+[[BlenderShortcuts.md]]
## To Do
[[Seam.md]]
+
+
diff --git a/BlenderShortcuts.md b/BlenderShortcuts.md
@@ -0,0 +1,40 @@
+:blender: :cs331:
+# Blender Shortcuts
+
+Shortcuts from lectures
+
+## Notes
+
+"Z" - Switch between solid and wireframe (useful to select everything from a mesh from all sides)
+
+"1" - Vertex Mode
+
+"2" - Edge Mode
+
+"3" - Face Mode
+
+"a" - Toggle select all when using the select box (top of left pane overlay)
+
+Transform operations:
+
+"g" - move selected items (translate) - pair this with x,y, and z to just move on the specified axis
+
+"r" - rotate selected parts - this also can be used with an axis using x,y, and z keys as done with translations.
+
+"s" - scale selected parts - see above for sepcifying axis movements
+
+Edit Mode:
+
+"e" - extrude the selected parts - you can still specify the axis to extrude by.
+
+"ctrl+R" - loop cut - create new verticies and edges around the circumference of the selected area. We can then subdivide further using the mouse wheel
+
+Forcing Bilateral Symmetry:
+
+In edit mode, select the object. In the right control panel select modifiers (blue wrench) and then add mirror over the expected axis.
+
+If you select "clipping" then it won't create the interior face. To do this drag them apart, click the button, and drag them back together.
+
+This does not work for armatures. Instead, you need to select the bones to mirror, right click, selecte autoname, right click again, select symmeterize. This will mirror over x axis. If you don't autoname it won't work, also if you don't have it mirroring over the x-axis, it will also not work. As such, to resolve the rotation issue, click "r" and then rotate to ensure it should be mirrored over the x-axis
+
+
diff --git a/ClusteringAlgorithms.md b/ClusteringAlgorithms.md
@@ -10,3 +10,7 @@ ML L1
Think google news group related stories amongst other things.
This is often done via [[UnsupervisedLearning.md]]
+
+An important distinction between this and [[ClassificationProblem.md]] is that clustering algorithms don't know the groupings before hand and are unsupervised. This means they know certain samples are similar, but does not have a term to describe said membership.
+
+Clustering algorithms can also be hierarchical where they have groupings and then subgroupings as well.
diff --git a/DimensionalityReduction.md b/DimensionalityReduction.md
@@ -0,0 +1,10 @@
+:ml:
+# Dimensionality Reduction
+
+ML CH1
+
+## Notes
+
+**Definition:** This is where you have the goal of reducing the required data without losing too much information. This is like lossy compression.
+
+This can be done by merging multiple correlated features into one. This is referred to as feature extraction where you extract a new feature from existing features to replace them.
diff --git a/Feature.md b/Feature.md
@@ -0,0 +1,12 @@
+:ml:
+# Feature
+
+ML CH1
+
+## Notes
+
+**Definition:** A feature is a ml term used to describe either an individual feature of a sample or a given feature of all samples.
+
+Example of one sample: The fuel economy feature of the toyota carolla is very high.
+
+Example of all samples: The fuel economy feature seems to be related to the rate of breakdown for cars.
diff --git a/KeyframeAnimation.md b/KeyframeAnimation.md
@@ -30,5 +30,3 @@ See [[Animation.md]] which is related to this topic.
The "Dope Sheet" is the sheet at the bottom of the screen that shows the timeline for keyframe rendering (this is blender specific, but maybe can be extrapolated).
When creating keyframe animations we select a frame from the dopesheet then we specify the pose at the given time. Rinse and repeat.
-
-
diff --git a/LinearRegression.md b/LinearRegression.md
@@ -9,3 +9,4 @@ ML L2 - Also referred to as ordinary least squares
The goal is to find a $\theta$ (parameters) that minimizes $J(\theta)=\frac{1}{2}\sum_{i=1}^{m}(h(x_i) - y_i)^2$. This is called the cost function.
+
diff --git a/LogisticRegression.md b/LogisticRegression.md
@@ -1 +1,10 @@
-:todo:
+:ml:
+# Logistic Regression
+
+ML CH1
+
+## Notes
+
+**Definition:** Logistic regression is the process of assigning a probablility of an item being part of a given class.
+
+This is a [[RegressionProblem.md]] and a [[ClassificationProblem.md]] as it generates a continuous value to determine the classification of a piece of data.
diff --git a/MachineLearning.md b/MachineLearning.md
@@ -38,12 +38,19 @@ ML Categories:
Concepts:
[[RegressionProblem.md]]
+[[VisualizationAlgorithm.md]]
+[[DimensionalityReduction.md]]
+[[AnomalyDetection.md]]
+[[NoveltyDetection.md]]
[[LinearRegression.md]]
[[GradientDescent.md]]
[[ClassificationProblem.md]]
[[SupportVectorMachine.md]]
[[ClusteringAlgorithms.md]]
[[EigenVector.md]]
+[[NLP.md]]
+[[NLU.md]]
+[[Feature.md]]
To do:
diff --git a/NLP.md b/NLP.md
@@ -0,0 +1,8 @@
+:ml:
+# NLP
+
+ML Book CH1
+
+## Notes
+
+**Definition:** NLP is the acronym for natural language processing. This is the process of taking in language data (written, audible, or some other form), and doing something with it. This may be classification or something else.
diff --git a/NLU.md b/NLU.md
@@ -0,0 +1,8 @@
+:ml:
+# NLU
+
+ML CH1
+
+## Natural Language Understanding
+
+**Definition:** NLU is an application of ML where the model must in some way interpret input language data.
diff --git a/NoveltyDetection.md b/NoveltyDetection.md
@@ -0,0 +1,10 @@
+:ml:
+# Novelty Detection
+
+ML CH1
+
+## Notes
+
+**Definition:** Novelty detection is used to detect new samples that appear different from other instances in the training set.
+
+This is similar to [[AnomalyDetection.md]].
diff --git a/RegressionProblem.md b/RegressionProblem.md
@@ -9,4 +9,6 @@ ML L1
Yes/no problem is a [[ClassificationProblem.md]].
-Also see for a more specific example [[LinearRegression.md]]
+Also see for a more specific example [[LinearRegression.md]]. There are other types of regression as well such as polynomial regression (no note at this time).
+
+When discussing regression, we often use the term "target" instead of "label" to describe the desired output. This contrasts with classification problems where we use the term label.
diff --git a/SupervisedLearning.md b/SupervisedLearning.md
@@ -9,4 +9,4 @@ ML L1
Most widely used form of model training.
-
+These desired outputs are referred to as labels. The inputs are referred to as instances.
diff --git a/UnsupervisedLearning.md b/UnsupervisedLearning.md
@@ -10,5 +10,3 @@ ML L1
[[ClusteringAlgorithms.md]] are often created using unsupervised learning.
Another example of unsupervised learning is the cocktail party problem where you have multiple microphones in a room that is noisy, how do you separate out individual voices?
-
-
diff --git a/VisualizationAlgorithm.md b/VisualizationAlgorithm.md
@@ -0,0 +1,8 @@
+:ml:
+# Visualization Algorithms
+
+ML Ch1
+
+## Notes
+
+**Definition:** Visualization algorithms are [[UnsupervisedLearning.md]] algorithms that output 2D or 3D representations of your data.
diff --git a/index.md b/index.md
@@ -20,3 +20,4 @@ This is the index for my main note classifications. I will maintain this as a ho
- [ ] "The Structure of Scientific Revolutions" - Thomas Kuhn
- [ ] "Introduction to Computing Systems" - Patt and Patel
+- [ ] "Hands-On Machine Learning with Scikit-Learn and TensorFlow" - Aurelien Geron
