User contributions for Rice

1 May 2024

• 21:2121:21, 1 May 2024 diff hist 0‎ m First order scalar ODE ‎ Rice moved page First Order Scalar ODE to First order scalar ODE current
• 21:1821:18, 1 May 2024 diff hist +29‎ Ordinary differential equation ‎ →‎Solvable Classes
• 03:4803:48, 1 May 2024 diff hist +191‎ N Nondimensionalization ‎ Created page with "'''Nondimensionalization''' is a technique for simplifying equations, where the dependent variables are changed in such a way that constants are removed. An example would be logistic ODE."
• 03:4703:47, 1 May 2024 diff hist +72‎ N Logistic ODE ‎ Created page with "Solved by nondimensionalization Category:Differential Equations" current
• 03:2203:22, 1 May 2024 diff hist +31‎ Feed-forward pass ‎No edit summary current
• 03:2203:22, 1 May 2024 diff hist +271‎ N Feed-forward pass ‎ Created page with "The '''feed-forward pass''' is the process of obtaining the result of a neural network. The input is fed into the network, which transforms it layer-by-layer, each layer ''feeding'' its computed results ''forward'' to the next layer until the output layer is reached." Tag: Visual edit
• 03:2003:20, 1 May 2024 diff hist +176‎ Neural network ‎ →‎Loss function Tag: Visual edit
• 03:1803:18, 1 May 2024 diff hist +902‎ N Back propagation ‎ Created page with "'''Back propagation''' is a error calculation technique. It consists of passing a loss function ''backwards'' through a neural network layer-by-layer to update its weights. = Procedure = Consider the following RSS loss function (halved for easier derivative). <math> E = \frac{1}{2}\sum (y_i - \bf{w}\bf{x})^2 </math> After each feed-forward pass where one data point is passed through the neural network, the gradient of the loss function is computed. We compute gra..." current
• 01:1501:15, 1 May 2024 diff hist +205‎ Neural network ‎ →‎Constraints
• 00:2400:24, 1 May 2024 diff hist +535‎ Neural network ‎ →‎Classification
• 00:2200:22, 1 May 2024 diff hist +86‎ One-hot encoding ‎No edit summary current Tag: Visual edit
• 00:2200:22, 1 May 2024 diff hist +182‎ N Label encoding ‎ Created page with "'''Label encoding''' encodes ordinal categorical data into numerical ones by representing them as discrete numbers. It does not work for nominal data. Category: Machine Learning" current
• 00:2100:21, 1 May 2024 diff hist +147‎ N One-hot encoding ‎ Created page with "'''One-hot encoding''' encodes nominal categorical data into numerical ones by representing them as binary vectors. Category: Machine Learning"
• 00:1500:15, 1 May 2024 diff hist +31‎ Activation function ‎No edit summary current
• 00:1500:15, 1 May 2024 diff hist +423‎ N Activation function ‎ Created page with "The '''activation function''' determines the output of a neuron in a neural network. It generates the output of the neuron from the linear combination of inputs calculated by the neuron. The choice of activation function varies depending on the machine learning task. A simple linear activation function or no activation function is just linear regression. A sigmoid function can be used for a classification task."
• 00:1400:14, 1 May 2024 diff hist +31‎ N Linear Regression ‎ Rice moved page Linear Regression to Linear regression current Tag: New redirect
• 00:1400:14, 1 May 2024 diff hist 0‎ m Linear regression ‎ Rice moved page Linear Regression to Linear regression

30 April 2024

• 23:5223:52, 30 April 2024 diff hist −691‎ Artificial neural network ‎No edit summary current Tag: Visual edit: Switched
• 23:5223:52, 30 April 2024 diff hist +287‎ Neural network ‎No edit summary
• 23:5023:50, 30 April 2024 diff hist +1,391‎ N Neural network ‎ Created page with "A '''neural network''' is a type of machine learning model that utilizes layers of connected '''neurons''' to perform classification and regression. = Structure = == Neuron == The '''neuron''' is the data-processing unit that composes a neural network. It combines information from multiple neurons (or input) and become activated or deactivated. The output is determined by the following steps: # A neuron generates a linear combination of input data, ''z''. This is done..."
• 23:3923:39, 30 April 2024 diff hist +445‎ Artificial neural network ‎ →‎Loss function Tag: Visual edit: Switched
• 23:3123:31, 30 April 2024 diff hist +147‎ Artificial neural network ‎No edit summary Tag: Visual edit
• 23:3123:31, 30 April 2024 diff hist +20‎ N File:Covex vs. Non-convex.png ‎No edit summary current
• 23:3023:30, 30 April 2024 diff hist +792‎ N Artificial neural network ‎ Created page with "An '''artificial neural network (ANN)''' is a machine learning algorithm that uses three layers of neurons to perform classification/regression. = Structure = All ANN's consist of three layers of neurons: the input layer, the hidden layer, and the output layer. The number of neurons in each layer determines the complexity of the model, with a larger layer indicating a more complicated model. Each neuron takes in information from neurons of the previous layer (and for t..."
• 23:2423:24, 30 April 2024 diff hist +80‎ Perceptron learning ‎No edit summary current

29 April 2024

• 19:5119:51, 29 April 2024 diff hist +60‎ SR latch ‎No edit summary
• 15:4215:42, 29 April 2024 diff hist +223‎ SR latch ‎No edit summary
• 15:3515:35, 29 April 2024 diff hist +231‎ N SR latch ‎ Created page with "thumb|Figure 1. SR latch circuit and truth table The '''set-reset latch''' is a circuit that stores a value in a bistable circuit using two NOR gates. It is the fundamental building block for memory cells." Tag: Visual edit
• 15:3415:34, 29 April 2024 diff hist +71‎ N File:SR Latch.png ‎No edit summary current
• 15:1815:18, 29 April 2024 diff hist +148‎ N Astable ‎ Created page with "'''Astable''' circuits do not have a stable state. An example would be a clock, which fluctuates between 0 and 1. Category:Computer Architecture" current Tag: Visual edit
• 15:1715:17, 29 April 2024 diff hist +128‎ N Bistable ‎ Created page with "A '''bistable''' circuit has two stable states. Think of two NOT gates feedbacking in a loop. Category:Computer Architecture" current Tag: Visual edit

27 April 2024

• 21:3321:33, 27 April 2024 diff hist +3,076‎ JSON Web Token ‎No edit summary current Tag: Visual edit

26 April 2024

• 22:2722:27, 26 April 2024 diff hist +938‎ N Existence-uniqueness ‎ Created page with "Consider an IVP for a general first order scalar ODE. <math> \begin{cases} y' = f(t,y)\\ y(t_0) = y_0 \end{cases} </math> The '''existence-uniqueness theorem''' theorem states that if <math>f(t,y)</math> and its derivative w.r.t. y is continuous in some rectangle <math>a<t<b</math>, <math>c<y<d</math> about <math>(t_0, y_0)</math>, then there exists a unique solution of the IVP defined for some time interval <math>a'<t<b'</math> about..."
• 15:2915:29, 26 April 2024 diff hist +149‎ ALU ‎No edit summary current
• 15:2715:27, 26 April 2024 diff hist +47‎ ALU ‎No edit summary
• 06:5706:57, 26 April 2024 diff hist +137‎ Curve fitting ‎ →‎Overfitting Tag: Visual edit
• 06:4906:49, 26 April 2024 diff hist +48‎ Machine Learning ‎ →‎Classifications current
• 06:4806:48, 26 April 2024 diff hist +101‎ Outlier ‎No edit summary current Tag: Visual edit
• 06:4706:47, 26 April 2024 diff hist +21‎ N Outliers ‎ Rice moved page Outliers to Outlier current Tag: New redirect
• 06:4706:47, 26 April 2024 diff hist 0‎ m Outlier ‎ Rice moved page Outliers to Outlier
• 06:4706:47, 26 April 2024 diff hist +48‎ Skewness ‎ →‎Detection current
• 06:4606:46, 26 April 2024 diff hist +121‎ Skewness ‎No edit summary Tag: Visual edit
• 06:4506:45, 26 April 2024 diff hist +133‎ N File:Skewness mitigation.png ‎No edit summary current
• 06:4406:44, 26 April 2024 diff hist +663‎ N Skewness ‎ Created page with "The '''skewness''' of a dataset determines the direction of the outliers. = Impact = Many models assume the data to be normally distributed. Skewed data in those models will result in inaccurate predictions. = Detection = Data skewness is detected during Exploratory data analysis. The first method is visualization. Just look at a graph lol. Numerically, in a dataset, if the median < the mean, then it is skewed to the right. Vice versa. = Mitigate pr..."
• 06:4006:40, 26 April 2024 diff hist +409‎ N Outlier ‎ Created page with "Outliers are samples that show abnormal distance from other samples. They impact the accuracy of the model. Outliers are detected during Exploratory data analysis. Several detection methods are listed. *Background knowledge such as impossible values like negative age *Visualization such as scatter plot *Data Analysis such as box plot *ML algorithms such as One-Class-SVM Category:Machine Learning"
• 06:3706:37, 26 April 2024 diff hist +235‎ Dataset ‎ →‎Usage attributes current
• 06:3006:30, 26 April 2024 diff hist −95‎ Exploratory data analysis ‎No edit summary Tag: Visual edit
• 06:2906:29, 26 April 2024 diff hist +235‎ Dataset ‎ →‎Attributes of a dataset
• 06:2206:22, 26 April 2024 diff hist +580‎ N Dataset ‎ Created page with "In machine learning, a model operates on a '''dataset'''. = Attributes of a dataset = The '''completeness''' of a dataset is the extent to which it contains all relevant '''features''' necessary for a given task. A dataset needs to have a sufficient number of observations, measured by the '''size''' of the dataset. The '''validity''' of the dataset is how accurate, clean, and relevant the data in the dataset is. A dataset can be '''high dimensional''', meaning that i..."
• 06:1606:16, 26 April 2024 diff hist +51‎ Machine Learning ‎ →‎Constructing ML Models